Professor Gustavo Carneiro
Professor of AI and Machine Learning
Academic and research departments
Centre for Vision, Speech and Signal Processing (CVSSP), Department of Electrical and Electronic Engineering.About
Biography
Gustavo Carneiro is a Professor of AI and Machine Learning at the University of Surrey, UK. Before that, from 2019 to 2022, he was a Professor at the School of Computer Science at the University of Adelaide, an ARC Future Fellow, and the Director of Medical Machine Learning at the Australian Institute of Machine Learning. He joined the University of Adelaide as a senior lecturer in 2011, has become an associate professor in 2015 and a professor in 2019. In 2014 and 2019, he joined the Technical University of Munich as a visiting professor and a Humboldt fellow. From 2008 to 2011 Dr. Carneiro was a Marie Curie IIF fellow and a visiting assistant professor at the Instituto Superior Tecnico (Lisbon, Portugal) within the Carnegie Mellon University-Portugal program (CMU-Portugal). From 2006 to 2008, Dr. Carneiro was a research scientist at Siemens Corporate Research in Princeton, USA. In 2005, he was a post-doctoral fellow at the University of British Columbia and at the University of California San Diego. Dr. Carneiro received his Ph.D. in computer science from the University of Toronto in 2004.
Areas of specialism
Machine Learning; Computer Vision; Medical Image Analysis
My qualifications
2004
PhD
University of Toronto, Canada
1999
MSc
Instituto Militar de Engenharia, Brazil
1996
BSc
Universidade Federal do Rio de Janeiro, Brazil
Previous roles
01 January 2019 - 30 November 2022
Full Professor
University of Adelaide, Australia
01 March 2019 - 30 June 2019
Humboldt Fellow
Technical University of Munich, Germany
01 March 2020 - 30 November 2022
Australian Research Council Future Fellow
University of Adelaide, Australia
01 August 2014 - 31 January 2015
Humboldt Fellow
Technical University of Munich, Germany
01 January 2018 - 30 November 2022
Director of Medical Machine Learning at the Australian Institute for Machine Learning
University of Adelaide, Australia
01 January 2015 - 31 December 2018
Associate Professor
University of Adelaide, Australia
17 July 2011 - 31 December 2014
Senior Lecturer
University of Adelaide, Australia
01 January 2010 - 15 July 2011
Marie Curie International Incoming Fellow
Instituto Superior Tecnico, Portugal
15 September 2008 - 31 December 2009
CMU-Portugal Visiting Professor
Instituto Superior Tecnico, Portugal
01 January 2006 - 05 September 2008
Senior Research Scientist
Siemens Corporate Research
01 January 2005 - 31 December 2005
NSERC Post-doctoral Fellow
University of British Columbia, Canada
15 September 2004 - 15 December 2004
Post-doctoral Fellow
University of California, San Diego
News
In the media
University of Adelaide using machine learning for endometriosis diagnosis
Interviewee
The Advertiser, Australia
Aussie Robotics researchers say their work is ‘revolutionising’ the health sector
Interviewee
IT Wire
AI-based breast cancer detection method inspired by a classic video game
Interviewee
Radiology Business
When are you going to die? Artificial Intelligence could tell you
Supervisor of L. Oakden- Rayner, the interviewee
The Technews
ResearchResearch interests
I have a wide-range of research interests. I am interested in applied research in medical image analysis and computer vision to theoretical research in machine learning.
Research projects
Development of new machine learning tools to help with the diagnosis of endometriosis from MRI and ultrasound
Development of new machine learning tools to allow the training of models using poorly curated training sets
Development of new medical image analysis methods for survival analysis and visual biomarker discovery
Development of new medical image analysis methods that can diagnose breast cancer from mammograms and MRI
One of the first methods in the field to use deep learning for the detection and segmentation of the left ventricle of the heart from ultrasound
Development of new deep learning methods for the quantification of tumour hypoxia from multi-modal microscopy images using weakly-supervised learning methods
Robotic Vision Australia is a national community of researchers and professionals, passionate about the potential for robotics, computer vision and AI to solve many of the world’s grand challenges. Robotic Vision Australia has been established to lead an agenda around Australia’s uptake of these innovative technologies and what we need to do to realise our potential as world leaders in this field.
This is a project that gathers researchers from the Instituto Superior Técnico, the Faculdade de Letras da Universidade de Lisboa, and the Museu Nacional do Azulejo with the purpose of designing a software to aid the study and the identification of Portuguese tile art.
Mainly due to the ease of reproduction and transportation, prints were used as the favoured means to make pictures and information available throughout the world. In this way, these art works quickly reached the hands of craftsman which used them as sources of inspiration, replicating them in different media, among which the tiles are particularly noteworthy. Trademark of Portuguese culture, the tiles have been produced continuously for five centuries, benefiting from the original prints in composition and theme, but using them freely; changing proportions, adding and removing figures, simplifying or enriching backgrounds, inverting figures, among other things.
The project aims to develop a tool that enables the cross-reference of information, matching prints and tiles, so as to identify the original sources of any given panel, as well as matching the tile panels and the figures portrayed in them. Another goal of the project is the creation of an annotated database, which will be available to help future research on Portuguese tile art.
Research interests
I have a wide-range of research interests. I am interested in applied research in medical image analysis and computer vision to theoretical research in machine learning.
Research projects
Development of new machine learning tools to help with the diagnosis of endometriosis from MRI and ultrasound
Development of new machine learning tools to allow the training of models using poorly curated training sets
Development of new medical image analysis methods for survival analysis and visual biomarker discovery
Development of new medical image analysis methods that can diagnose breast cancer from mammograms and MRI
One of the first methods in the field to use deep learning for the detection and segmentation of the left ventricle of the heart from ultrasound
Development of new deep learning methods for the quantification of tumour hypoxia from multi-modal microscopy images using weakly-supervised learning methods
Robotic Vision Australia is a national community of researchers and professionals, passionate about the potential for robotics, computer vision and AI to solve many of the world’s grand challenges. Robotic Vision Australia has been established to lead an agenda around Australia’s uptake of these innovative technologies and what we need to do to realise our potential as world leaders in this field.
This is a project that gathers researchers from the Instituto Superior Técnico, the Faculdade de Letras da Universidade de Lisboa, and the Museu Nacional do Azulejo with the purpose of designing a software to aid the study and the identification of Portuguese tile art.
Mainly due to the ease of reproduction and transportation, prints were used as the favoured means to make pictures and information available throughout the world. In this way, these art works quickly reached the hands of craftsman which used them as sources of inspiration, replicating them in different media, among which the tiles are particularly noteworthy. Trademark of Portuguese culture, the tiles have been produced continuously for five centuries, benefiting from the original prints in composition and theme, but using them freely; changing proportions, adding and removing figures, simplifying or enriching backgrounds, inverting figures, among other things.
The project aims to develop a tool that enables the cross-reference of information, matching prints and tiles, so as to identify the original sources of any given panel, as well as matching the tile panels and the figures portrayed in them. Another goal of the project is the creation of an annotated database, which will be available to help future research on Portuguese tile art.
Supervision
Postgraduate research supervision
I am currently supervising the following students and postdocs from the University of Adelaide
- Adrian Galdran (Marie Curie Research Fellow at the Universitat Pompeu Fabra and University of Adelaide)
- Hu Wang (Research Associate at the University of Adelaide, main supervisor)
- Cuong Cao Nguyen (Research Associate at the University of Adelaide, main supervisor)
- Fengbei Liu (Ph.D. at the University of Adelaide, main supervisor)
- Yuyuan Liu (Ph.D. at the University of Adelaide, main supervisor)
- Yuanhong Chen (Ph.D. student at the University of Adelaide, main supervisor)
- Chong Wang (Ph.D. student at the University of Adelaide, main supervisor)
- Yuan Zhang (Ph.D. student at the University of Adelaide, main supervisor)
- Arpit Garg (Ph.D. student at the University of Adelaide, main supervisor)
- Dileepa Pitawela (Ph.D. student at the University of Adelaide, co-supervisor)
- Dung Anh Hoang (MPhil at the University of Adelaide, main supervisor)
Postgraduate research supervision
I successfully supervised the following students and postdocs:
- Renato Hermoza Aragones (Ph.D. at the University of Adelaide, graduated in September 2022 - received the Dean’s Commendation for Doctoral Thesis Excellence - Congrats Renato)
- Yu Tian (Ph.D. at the University of Adelaide, graduated in June 2022)
- Lauren Oakden-Rayner (Ph.D. at the University of Adelaide, graduated in March 2022 - received the Dean’s Commendation for Doctoral Thesis Excellence - Congrats Lauren)
- Cuong Cao Nguyen (Ph.D. at the University of Adelaide, graduated in February 2022)
- Brandon Smart (Honour student at the University of Adelaide, graduated in December 2021)
- Alireza Seyed Shakeri (Master student at the University of Adelaide, finish project in December 2021)
- Hossein Askari (MPhil at the University of Adelaide, main supervisor, graduated in October 2021)
- Artur Banach (Ph.D. student at Queensland University of Technology, graduated in October 2021)
- Yuan Zhang (Master student at the University of Adelaide, graduated in July 2021)
- Wenping Du (Master student at the University of Adelaide, graduated in July 2021)
- Gabriel Maicas (Research Associate at the University of Adelaide from 2019 to 2021, main supervisor)
- Ragav Sachdeva (Honour student at the University of Adelaide, graduated in December 2020)
- Yuanhong Chen (Honour student at the University of Adelaide, graduated in December 2020)
- Hoang Son Le (Honour student at the University of Adelaide, graduated in December 2020)
- Zachri Prinsloo (Honour student at the University of Adelaide, graduated in December 2020)
- Filipe Cordeiro (Prof. from UFRPE-Brazil, spent a sabbatical leave at the University of Adelaide from 2019 to 2020)
- Adrian Johnston (Ph.D. at the University of Adelaide, graduated in September 2020)
- Fabio Faria (Prof. from UNIFESP-Brazil, spent a sabbatical leave at the University of Adelaide from 2019 to 2020)
- Michele Sasdelli (Research Associate at the University of Adelaide from 2018 to 2020)
- Leonardo Zorron Cheng Tao Pu (Ph.D. at the University of Adelaide, graduated in July 2020 - received the Dean’s Commendation for Doctoral Thesis Excellence - Congrats Leo)
- Sam Karem (Master student at the University of Adelaide, graduated in July 2020)
- Aniruddha Biswas (Master student at the University of Adelaide, graduated in July 2020)
- Rafael Felix (Ph.D. at the University of Adelaide, graduated in February 2020 - received the Dean’s Commendation for Doctoral Thesis Excellence - Congrats Rafael!)
- Toan Minh Tran (Ph.D. at the University of Adelaide, graduated in January 2020)
- Fengbei Liu (Honours at the University of Adelaide, graduated in December 2019)
- Yuyuan Liu (Honours at the University of Adelaide, graduated in December 2019)
- Saskia Glaser (Master student at the University of Adelaide, graduated in December 2019)
- Farbod Motlagh (Honours at the University of Adelaide, graduated in July 2019)
- Jerome Williams (MPhil at the University of Adelaide, graduated in August 2019)
- Yu Tian (Honours student at the University of Adelaide - graduated in December 2018)
- Gabriel Maicas (Ph.D. at the University of Adelaide, graduated in December 2018 - received the Dean’s Commendation for Doctoral Thesis Excellence - Congrats Gabriel!)
- Vijay Kumar (Post-doc at the University of Adelaide from 2016 to 2018 - now at Xerox PARC)
- William Gale (Honours student at the University of Adelaide - graduated in December 2017, working at Microsoft Research. William was awarded the National iAwards for Undergraduate Tertiary Students for his honours project - Congrats William!)
- Zhibin Liao (Ph.D. at the University of Adelaide - graduated in September 2017 - After graduation, went to a postdoc at the University of British Columbia)
- Christian Lee (Masters student at the University of Adelaide - graduated in August 2017)
- Andrew Lang (Honours student at the University of Adelaide - graduated in November 2016) - check video of Andrew's project!
- Neeraj Dhungel (Ph.D. at the University of Adelaide - graduated in October 2016 - Now a postdoc at the University of British Columbia)
- Zhi Lu (Visiting Ph.D student in 2013 and Post-Doc at the University of Adelaide in 2014-2015. Now a post-doc at the University of South Australia)
- Tuan Anh Ngo (Ph.D. at the University of Adelaide - graduated in August 2015 - received the Dean’s Commendation for Doctoral Thesis Excellence. Now a Professor at the Vietnam National University of Agriculture)
- Tom Schultz (Honours student at the University of Adelaide - graduated in December 2014)
- Ren Ding (Honours student at the University of Adelaide - graduated in July 2014)
- Qian Chen (Masters student at the University of Adelaide - graduated in July 2014)
- Zhe Yin (Masters student at the University of Adelaide - graduated in July 2014)
- Zhibin Liao (Honours at the University of Adelaide - graduated in July/2013. Now a Ph.D. student)
- Xuance Wang (Honours at the University of Adelaide - graduated in December 2013)
- Danilo Dell'Agnello (Post Doc at the University of Adelaide in 2012-13)
- Nuno Miguel Pinho da Silva (Post Doc at the Instituto Superior Tecnico, University of Lisbon in 2011-12).
- Joao Tiago Fonseca (M.Sc. at the Instituto Superior Tecnico, Technical University of Lisbon in 2011-12)
- Michael Wels (Siemens Ph.D. Student in 2008). Now at Siemens Healthcare.
- Fernando Amat (Siemens Intern in 2007). Now at Janelia Farm Research Campus.
- Guillaume Heusch (Siemens Intern in 2007-08).
Teaching
Courses I taught at the University of Adelaide, Australia
- Grand Challenges in Computer Science (S2, 2022)
- Grand Challenges in Computer Science (S2, 2021)
- Grand Challenges in Computer Science (S2, 2020)
- Topics in Computer Science (S2, 2019)
- Grand Challenges in Computer Science (S2, 2019)
- Topics in Computer Science (S2, 2018)
- Grand Challenges in Computer Science (S2, 2018)
- Topics in Computer Science (S1, 2018)
- Puzzle-based Learning (S1, 2018)
- Artificial Intelligence (S1, 2018)
- Computer Graphics (S1, 2018) - Videos of Best Projects
- Grand Challenges (S2, 2018)
- Topics in Computer Science (Spring 2017)
- Computer Graphics (Fall 2017) - Videos of Best Projects
- Topics in Computer Science (Fall 2017)
- Advanced Topics in Computer Science (Fall 2017)
- Puzzle-Based Learning (Fall 2017)
- Introduction to Geometric Programming (Spring 2016)
- Topics in Computer Science (Spring 2016)
- Puzzle-Based Learning (Fall 2016)
- Topics in Computer Science (Fall 2016)
- Object Oriented Programming (Spring 2015)
- Topics in Computer Science (Spring 2015)
- Computer Graphics (Fall 2015) - Videos of Best Projects
- Puzzle-Based Learning (Fall 2015)
- Topics in Computer Science (Fall 2015)
- Puzzle-Based Learning (Fall 2014)
- Software Engineering in Industry (Fall 2014)
- Topics in Computer Science (Fall 2014)
- Puzzle-Based Learning (Spring 2013)
- Software Engineering Group Project 1B (Spring 2013)
- Master of Software Engineering Project (Spring 2013)
- Computer Graphics (Fall 2013) - Videos of Best Projects
- Puzzle-Based Learning (Fall 2013)
- Puzzle-Based Learning (Spring 2012)
- Computer Vision (Fall 2012)
- Computer Graphics (Fall 2012) - Videos of Best Projects
Courses I taught at the Instituto Superior Tecnico, Portugal
- Signals and Systems (Fall 2009)
- Robotics (Spring 2009)
- Modeling and Simulation (Spring 2009)
- Signal Processing (Fall 2008)
- Control (Fall 2008)
Courses I taught at the University of Toronto, Canada
- CSC 324 - Principles of Programming Languages (Fall 2004)
- CSC 446, Computer Methods for Partial Differential Equations (TA) (Winter 2002).
- CSC 418, Computer Graphics (TA) (1999-2003).
- CSC 458, Computer Networks (TA) (Winter 2000).
- CSC 258, Computer Organization (TA) (Summer 2000).
- CSC 260, An Introduction to Scientific, Symbolic, and Graphical Computation (TA) (Winter 2003).
- SCI 199, Computer and Images. (TA) (2000-2001)
Publications
Additional publications
2023
- Ragav Sachdeva, Filipe Rolim Cordeiro, Vasileios Belagiannis, Ian Reid, and Gustavo Carneiro. ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning. Pattern Recognition 134 (2023): 109121.[pdf]
- Hu Wang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, and Gustavo Carneiro. Multi-Modal Learning With Missing Modality via Shared-Specific Feature Modelling. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 15878-15887. 2023. [pdf]
- Cuong C. Nguyen, Youssef Dawoud, Thanh-Toan Do, Jacinto C. Nascimento, Vasileios Belagiannis, and Gustavo Carneiro. Smart task design for meta learning medical image analysis systems: Unsupervised, weakly-supervised, and cross-domain design of meta learning tasks. In Meta-Learning with Medical Imaging and Health Informatics Applications, pp. 185-209. Academic Press, 2023.
- Brandon Smart, and Gustavo Carneiro (2023). Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 5344-5354. 2023.[pdf]
- Arpit Garg, Cuong Nguyen, Rafael Felix, Thanh-Toan Do, and Gustavo Carneiro (2023). Instance-Dependent Noisy Label Learning via Graphical Modelling. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 2288-2298. 2023.[pdf]
- Youssef Dawoud, Arij Bouazizi, Katharina Ernst, Gustavo Carneiro, and Vasileios Belagiannis (2023). Knowing What to Label for Few Shot Microscopy Image Cell Segmentation. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3568-3577. 2023.[pdf]
- Y Zhang, H Wang , D Butler, M To, J Avery, L Hull, G Carneiro. Distilling Missing Modality Knowledge from Ultrasound for Endometriosis Diagnosis with Magnetic Resonance Images International Symposium on Biomedical Imaging 2023 (ISBI 2023, *Best Oral Paper Award )
2022
- Cuong Nguyen, Thanh-Toan Do, and Gustavo Carneiro. PAC-Bayes meta-learning with implicit task-specific posteriors. In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022. [pdf]
- Filipe R. Cordeiro, Ragav Sachdeva, Vasileios Belagiannis, Ian Reid, and Gustavo Carneiro. Longremix: Robust learning with high confidence samples in a noisy label environment. Pattern Recognition (2022): 109013. [pdf]
- Fengbei Liu, Yu Tian, Yuanhong Chen, Yuyuan Liu, Vasileios Belagiannis, and Gustavo Carneiro. ACPL: Anti-curriculum Pseudo-labelling forSemi-supervised Medical Image Classification.Conference on Computer Vision and Pattern Recognition (CVPR) 2022. [pdf][Video]
- Yuyuan Liu, Yu Tian, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro. Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation. Conference on Computer Vision and Pattern Recognition (CVPR) 2022. [pdf][Video]
- Yu Tian, Yuyuan Liu, Guansong Pang, Fengbei Liu, Yuanhong Chen, and Gustavo Carneiro. Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes. European Conference on Computer Vision (ECCV) 2022 [pdf] (Oral presentation)
- Hu Wang, Jianpeng Zhang, Yuanhong Chen, Congbo Ma, Jodie Avery, Louise Hull, Gustavo Carneiro. Uncertainty-aware Multi-modal Learning via Cross-modal Random Network Prediction. European Conference on Computer Vision (ECCV) 2022 [pdf]
- Yuanhong Chen, Yu Tian, Guansong Pang, and Gustavo Carneiro. Deep One-Class Classification via Interpolated Gaussian Descriptor. AAAI Conference on Artificial Intelligence (AAAI-22).[pdf][Video](Oral presentation)
- Frazer, H.M., Tang, J.S., Elliott, M.S., Kunicki, K.M., Hill, B., Karthik, R., Kwok, C.F., Peña-Solorzano, C.A., Chen, Y., Wang, C. Al-Qershi, O., Fox, S., Li, S., Makalic, E., Nguyen, T. L.,Schmidt, D., Basnayake, P., Lippey, J.L., Brotchie, P., Hopper, J.L., Carneiro, G.,McCarthy, D.J. ADMANI: Annotated Digital Mammograms and Associated Non-Image Datasets. Radiology: Artificial Intelligence, p.e220072. [pdf]
- Frazer, H.M., Pena-Solorzano, C.A., Kwok, C.F., Elliott, M., Chen, Y., Wang, C., BRAIx team, Lippey, J., Hopper, J., Brotchie, P. and Carneiro, G., 2022. AI integration improves breast cancer screening in a real-world, retrospective cohort study. medRxiv, pp.2022-11. [pdf]
- Fengbei Liu, Yuanhong Chen, Yu Tian, Yuyuan Liu, Chong Wang, Vasileios Belagiannis, Gustavo Carneiro. NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Yuanhong Chen, Hu Wang, Chong Wang, Yu Tian, Fengbei Liu, Yuyuan Liu, Michael Elliott, Davis McCarthy, Helen Frazer, Gustavo Carneiro. Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans, Gustavo Carneiro. Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Chong Wang, Yuanhong Chen, Yuyuan Liu, Yu Tian, Fengbei Liu, Davis McCarthy, Michael Elliott, Helen Frazer, Gustavo Carneiro. Knowledge Distillation to Ensemble Global and Interpretable Prototype-based Mammogram Classification Models. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Renato Hermoza Aragones, Gabriel Maicas, Jacinto Nascimento, Gustavo Carneiro. Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Adrian Galdran, Narmin Ghaffari Laleh, Katherine Jane Hewitt, Jakob Kather, Miguel Angel González Ballester, Gustavo Carneiro. Test Time Transform Prediction for Open Set Histopathological Image Recognition. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2022. [pdf]
- Lauren Oakden-Rayner, William Gale, Thomas A. Bonham, Matthew P. Lungren, Gustavo Carneiro, Andrew P. Bradley, and Lyle J. Palmer. Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study. The Lancet Digital Health 4, no. 5 (2022): e351-e358. [pdf]
- Jin Lin Tan, Mohamed Asif Chinnaratha, Richard Woodman, Rory Martin, Hsiang-Ting Chen, Gustavo Carneiro, and Rajvinder Singh. Diagnostic Accuracy of Artificial Intelligence (AI) to Detect Early Neoplasia in Barrett's Esophagus: A Non-comparative Systematic Review and Meta-Analysis. Frontiers in medicine 9 (2022). [pdf]
- Gerard Snaauw, Michele Sasdelli, Gabriel Maicas, Stephan Lau, Johan Verjans, Mark Jenkinson, and Gustavo Carneiro. Mutual information neural estimation for unsupervised multi-modal registration of brain images. 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2022). [pdf]
- David Butler, Yuan Zhang, Tim Chen, Seon Ho Shin, Rajvinder Singh, Gustavo Carneiro. In Defense of Kalman Filtering for Polyp Treacking from Colonoscopy Videos. International Symposium on Biomedical Imaging (ISBI) 2022.[pdf][Video]
- Luiz Buris, Daniel Pedronette, Joao Papa, Jurandy Almeida, Gustavo Carneiro, Fabio Faria. Mixup-based Deep Metric Learning Approaches for Incomplete Supervision. International Conference on Image Processing (ICIP). 2022. [pdf]
- Emeson Santana, Gustavo Carneiro, and Filipe R. Cordeiro. A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels.SIBGRAPI - Conference on Graphics, Patterns and Images (2022).[pdf]
- Ojas Mehta, Zhibin Liao, Mark Jenkinson, Gustavo Carneiro, Johan Verjans. Machine Learning in Medical Imaging – Clinical Applications and Challenges in Computer Vision. In: 3. Bauer, D.C., Wilson, L.O.W., Twine, N.A. (eds). Book chapter in Artificial Intelligence in Medicine: Applications, Limitations and Future Directions. Springer, Singapore. https://doi.org/10.1007/978-981-19-1223-8_5. 2022.
2021
- Sourav Garg, Niko Sünderhauf, Feras Dayoub, Douglas Morrison, Akansel Cosgun, Gustavo Carneiro, Qi Wu, Tat-Jun Chin, Ian Reid, Stephen Gould, Peter Corke. Semantics for Robotic Mapping, Perception and Interaction: A Survey. Foundations and Trends® in Robotics. 2020 Dec 22;8(1–2):1-224.[pdf]
- Carlos Santiago, Catarina Barata, Michele Sasdelli, Gustavo Carneiro, Jacinto Nascimento. LOW: Training Deep Neural Networks by Learning Optimal Sample Weights. Pattern Recognition (2021) [link]
- Yu Tian, Guansong Pang, Yuanhong Chen, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro. Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning. International Conference on Computer Vision (ICCV) 2021. [pdf]
- Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro. Probabilistic task modelling for meta-learning. Conference on Uncertainty in Artificial Intelligence (UAI) 2021. [pdf]
- Filipe R. Cordeiro, Vasileios Belagiannis, Ian Reid, Gustavo Carneiro. PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels. British Machine Vision Conference (BMVC) 2021. [pdf]
- Yaqub Jonmohamadi, Shahnevaz Ali, Fengbei Liu, Jonathan Roberts, Ross Crawford, Gustavo Carneiro, Ajay Pandey. 3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021. [pdf]
- Minh-Son To, Ian Sarno, Chee Chong, Mark Jenkinson, Gustavo Carneiro. Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021. [pdf]
- Yu Tian, Guansong Pang, Fengbei Liu, Seon Ho Shin, Johan W. Verjans, Rajvinder Singh, and Gustavo Carneiro. Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021. [pdf]
- Adrian Galdran , Gustavo Carneiro, Miguel Angel González Ballester. Balanced-MixUp for highly imbalanced medical image classification. International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2021. [pdf]
- Ragav Sachdeva, Filipe R. Cordeiro, Vasileios Belagiannis, Ian Reid, Gustavo Carneiro. EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels. Winter Conference on Applications of Computer Vision (WACV) 2021.[pre-print]
- Renato Hermoza Aragones, Gabriel Maicas Suso, Jacinto Nascimento, Gustavo Carneiro. Post-hoc Overall Survival Time Prediction from Brain MRI. International Symposium on Biomedical Imaging (ISBI) 2021. [pre-print]
- Michele Sasdelli, Thalaiyasingam Ajanthan, Tat-Jun Chin, and Gustavo Carneiro. A Chaos Theory Approach to Understand Neural Network Optimization. International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2021. [pdf]
- Hoang Son Le, Rini Akmeliawati, Gustavo Carneiro. Combining Data Augmentation and Domain Distance Minimisation to Reduce Domain Generalisation Error. International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2021.[pdf]
- Hoang Son Le, Rini Akmeliawati, Gustavo Carneiro (2021). Domain Generalisation with Domain Augmented Supervised Contrastive Learning. AAAI Conference on Artificial Intelligence. Student Abstract. 2021 [pdf].
- Tiing Leong Ang and Gustavo Carneiro. Artificial intelligence in gastrointestinal endoscopy. Journal of Gastroentorology and Hepatology (2021): 5-6. [link]
- Linh Nguyen, Cuong Cao Nguyen, Gustavo Carneiro, Heike Ebendorff-Heidepriem, Stephen Warren-Smith. Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference. Photonics Research, 2021.
- Sergei Bedrikovetski, Nagendra N Dudi-Venkata, Gabriel Maicas Warren Seow, Hidde M. Kroon, Gustavo Carneiro, James W. Moore, Tarik Sammour. Artificial intelligence for the diagnosis of lymph node metastases in patients with abdominopelvic malignancy: a systematic review and meta-analysis. Artificial Intelligence in Medicine, 2021.
- Artur Banach, Mario Strydom, Anjali Jaiprakash, Gustavo Carneiro, Anders Eriksson, Ross Crawford, and Aaron McFadyen. Visual Localisation for Knee Arthroscopy. International Journal of Computer Assisted Radiology and Surgery 16, no. 12 (2021): 2137-2145.[pdf]
2020
- Gustavo Carneiro, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Alastair Burt. Deep Learning Uncertainty and Confidence Calibration for the Five-class Polyp Classification from Colonoscopy. Medical Image Analysis (2020) [pre-print].
- Leonardo Zorron Cheng Tao Pu, Gabriel Maicas, Yu Tian, Takeshi Yamamura, Masanao Nakamura, Hiroto Suzuki, Gurfarmaan Singh, Khizar Rana, Yoshiki Hirooka, Alastair D. Burt, Mitsuhiro Fujishiro, Gustavo Carneiro, Rajvinder Singh. Computer-aided diagnosis for characterization of colorectal lesions: a comprehensive software including serrated lesions. Gastrointestinal Endoscopy (GIE) 2020. [pubmed link]
- Anelia Angelova, Gustavo Carneiro, Niko Sünderhauf, Jürgen Leitner4 (Editors)(2020). Special Issue on Deep Learning for Robotic Vision. International Journal of Computer Vision (2020). [link]
- Yaqub Jonmohamadi , Yu Takeda, Fengbei Liu , Fumio Sasazawa, Gabriel Maicas, Ross Crawford, Jonathan Roberts, Ajay Pandey, Gustavo Carneiro. Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning. IEEE Access (2020) [pre-print].
- Artur Banach, Mario Strydom, Anjali Jaiprakash, Ross Crawford, Gustavo Carneiro, Cameron Brown, Aaron McFadyen. Saliency improvement in feature-poor surgical environments using Local Laplacian of Specified Histograms. IEEE Access 2020.
- Maria Antico, Fumio Sasazawa, Yu Takeda, Anjali Tumkur Jaiprakash, M-L. Wille, Ajay Pandey, Ross Crawford, Gustavo Carneiro, and Davide Fontanarosa (2020). Bayesian CNN for segmentation uncertainty inference on 4D ultrasound images of the femoral cartilage for guidance in robotic knee arthroscopy. IEEE Access (2020).
- Ranasinghe I, Hossain S, Ali A, Horton D, Adams RJ, Aliprandi-Costa B, Bertilone C, Carneiro G, Gallagher M, Guthridge S, Kaambwa B. SAFety, Effectiveness of care and Resource use among Australian Hospitals (SAFER Hospitals): a protocol for a population-wide cohort study of outcomes of hospital care. BMJ open. 2020 Aug 1;10(8):e035446. [link]
- Adrian Johnston, Gustavo Carneiro. Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volume. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2020) [pre-print]
- Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento, Gustavo Carneiro. Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification. International Conference on Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) 2020 [pre-print][presentation]
- Yu Tian, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro. Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy. In International Conference on Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) 2020 [pre-print][video][presentation]
- Fengbei Liu, Yaqub Jonmohamadi, Gabriel Maicas, Ajay K. Pandey, and Gustavo Carneiro. Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy. In International Conference on Medical Imaging Computing and Computer-Assisted Intervention (MICCAI) 2020 [pre-print][video]
- Rafael Felix, Michele Sasdelli, Ian Reid, Gustavo Carneiro. Augmentation Network for Generalised Zero-Shot Learning. Asian Confence on Computer Vision (ACCV) 2020.[pre-print]
- Youssef Dawoud, Julia Hornauer, Gustavo Carneiro, Vasileios Belagiannis. Few-Shot Microscopy Image Cell Segmentation. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2020 [pre-print]
- Binh Nguyen, Binh Nguyen, Gustavo Carneiro, Erman Tjiputra, Quang Tran and Thanh-Toan Do. Deep Metric Learning Meets Deep Clustering: A Novel Unsupervised Approach for Feature Embedding. British Machine Vision Conference (BMVC) 2020 [link]
- Gabriel Maicas, Cuong Nguyen, Farbod Motlagh, Jacinto C Nascimento, Gustavo Carneiro. Unsupervised Task Design to Meta-Train Medical Image Classifiers. International Symposium on Biomedical Imaging (ISBI) 2020. [pre-print] [Video]
- Yuyuan Liu, Yu Tian, Gabriel Maicas, Leonardo ZCT Pu, Rajvinder Singh, Johan W Verjans, Gustavo Carneiro. Photoshopping Colonoscopy Video Frames. International Symposium on Biomedical Imaging (ISBI) 2020. [pre-print] [Video]
- Saskia Glaser, Gabriel Maicas, Sergei Bedrikovetski, Tarik Sammour, Gustavo Carneiro. Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT. International Symposium on Biomedical Imaging (ISBI) 2020. [pre-print] [Video]
- Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro. Uncertainty in Model-Agnostic Meta-Learning using Variational Inference. Winter Conference on Applications of Computer Vision (WACV ’20) [pre-print].
- David Hall, Feras Dayoub, John Skinner, Peter Corke, Gustavo Carneiro, Niko Sünderhauf. Probability-based detection quality (pdq): A probabilistic approach to detection evaluation. Winter Conference on Applications of Computer Vision (WACV ’20) [pre-print]
- Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro, Christopher Ré. Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging. ACM Conference on Health, Inference, and Learning (ACM CHIL) 2020. [pre-print]
- Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro. Similarity of Classification Tasks. Workshop on Meta-Learning (MetaLearn 2020) at Neurips 2020. [pdf]
- Rafael Felix, Michele Sasdelli, Ben Harwood, Gustavo Carneiro. Generalised Zero-shot Learning with Multi-modalEmbedding Spaces. International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2020. [pre-print]
- S.M. Camps, T. Houben, G. Carneiro, C. Edwards, M. Antico, M. Dunnhofer, E.G.H.J. Martens, J.A. Baeza, B.G.L. Vanneste, E.J. van Limbergen, P.H.N. de With, F. Verhaegen, D. Fontanarosa. Automatic quality assessment of transperineal ultrasound images of the male pelvic region using deep learning. Ultrasound in medicine & biology 46.2 (2020): 422-435. [pre-print]
- M. Antico, F. Sasazawa, M. Dunnhofer, S.M. Camps, A.T. Jaiprakash, A.K. Pandey, R. Crawford, G. Carneiro, D. Fontanarosa. Deep Learning based femoral cartilage automatic segmentation in ultrasound imaging for robotic knee arthroscopy. Ultrasound in medicine & biology 46.2 (2020): 422-435. [pre-print]
- Fabio Faria and Gustavo Carneiro. Why are Generative Adversarial Networks so Fascinating and Annoying?. 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI). IEEE, 2020.[pre-print]
- Filipe Cordeiro and Gustavo Carneiro. A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations? 2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI). IEEE, 2020. [pre-print]
2019
- Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian Reid, Gustavo Carneiro. Pre and post-hoc diagnosis and interpretation of malignancy from breast dce-mri. In Medical Image Analysis 58 (2019): 101562. [pdf] [Video] [Tweet]
- Dunnhofer, Matteo, Maria Antico, Fumio Sasazawa, Yu Takeda, Saskia Camps, Niki Martinel, Christian Micheloni, Gustavo Carneiro, and Davide Fontanarosa. Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images. Medical Image Analysis (2019): 101631. [pdf]
- Jacinto Nascimento, Gustavo Carneiro. One shot segmentation: unifying rigid detection and non-rigid segmentation using elastic regularization. In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019. [pdf]
- L. Lu, X. Wang, G. Carneiro, L. Yang (Editors). Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics. Book published by Springer in 2019 [link]
- Niko Sünderhauf, Feras Dayoub, David Hall, John Skinner, Haoyang Zhang, Gustavo Carneiro, Peter Corke. A probabilistic challenge for object detection. Invited paper by Nature Machine Intelligence 1 (9) Pages 443-443. [link]
- J. Verjans, W.B. Veldhuis, G. Carneiro, J.M. Wolterink, I. Išgum, T. Leiner (2019) Cardiovascular Diseases (invited book chapter). In: Ranschaert E., Morozov S., Algra P. (eds) Artificial Intelligence in Medical Imaging. Springer, Cham. [link]
- Toan Tran, Thanh-Toan Do, Ian Reid, Gustavo Carneiro. Bayesian Generative Active Deep Learning. International Conference on Machine Learning (ICML) 2019. [pdf]
- Thanh-Toan Do, Toan Tran, Ian Reid, Vijay Kumar, Tuan Hoang, Gustavo Carneiro. A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning. Conference on Computer Vision and Pattern Recognition (CVPR) 2019. [pdf]
- Yu Tian, Leonardo Z.C.T. Pu, Rajvinder Singh, Alastair D. Burt, Gustavo Carneiro. One-stage Five-class Polyp Detection and Classification. International Symposium on Biomedical Imaging (ISBI) 2019. [pdf]
- Gabriel Maicas, Gerard Snaauw, Andrew Bradley, Ian Reid, Gustavo Carneiro. Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI. International Symposium on Biomedical Imaging (ISBI) 2019. [preprint]
- Gerard Snaauw, Dong Gong, Gabriel Maicas, Anton Van Den Hengel, Wiro Niessen, Johan Verjans, Gustavo Carneiro. End-to-End Diagnosis and Segmentation Learning from Cardiac Magnetic Resonance Imaging. International Symposium on Biomedical Imaging (ISBI) 2019. [preprint]
- William Gale, Gustavo Carneiro, Luke Oakden-Rayner, Lyle Palmer, Andrew Bradley. Producing radiologist quality reports for interpretable deep learning. International Symposium on Biomedical Imaging (ISBI) 2019. [preprint]
- Rafael Felix, Ben Harwood, Michele Sasdelli and Gustavo Carneiro. Generalised Zero-Shot Learning with Domain Classification in a Joint Semantic and Visual Space. International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2019 [pre-print]
- Adrian Johnston and Gustavo Carneiro. Single View 3D Point Cloud Reconstruction using Novel View Synthesis and Self-Supervised Depth Estimation. International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2019 [pre-print].
- L Pu, Zorron Cheng Tao, G Maicas, Y Tian, T Yamamura, G Singh, K Rana, H Suzuki, M Nakamura, Y Hirooka, A Burt, M Fujishiro, G Carneiro, R Singh. Prospective study assessing a comprehensive computer-aided diagnosis for characterization of colorectal lesions: Results from different centers and imaging technologies. In Journal of Gastroenterology and Hepatology, vol. 34, pp. 25-26. 2019. [link]
2018
- Zhibin Liao, Tom Drummond, Ian Reid, Gustavo Carneiro. Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks. In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018. [preprint]
- Rafael Felix, Vijay Kumar B G, Ian Reid, Gustavo Carneiro. Multi-modal Cycle-consistent Generalized Zero-Shot Learning. European Conference on Computer Vision (ECCV) 2018. [preprint]
- Trung Pham, Vijay Kumar B G, Thanh-Toan Do, Gustavo Carneiro, Ian Reid. Bayesian Instance Segmentation in Open Set World. European Conference on Computer Vision (ECCV) 2018. [preprint]
- Gabriel Maicas, Andrew Bradley, Jacinto Nascimento, Ian Reid, Gustavo Carneiro. Training Medical Image Analysis Systems like Radiologists. International Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI) 2018. [preprint].
- Saskia M. Camps, Tim Houben, Davide Fontanarosa, Christopher Edwards, Maria Antico, Matteo Dunnhofer, Esther G.H.J. Martens, Jose A. Baeza, Ben G.L. Vanneste, Evert J. van Limbergen, Peter H.N. de With, Frank Verhaegen, Gustavo Carneiro. One-class Gaussian process regressor for quality assessment of transperineal ultrasound images. International conference on Medical Imaging with Deep Learning (MIDL) 2018. [link]
- Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu & Vasileios Belagiannis (2018) 1st MICCAI workshop on deep learning in medical image analysis, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 6:3, 241-242, DOI: 10.1080/21681163.2018.1457242
- L.Z.C.T. Pu, B. Campbell, A.D. Burt, G. Carneiro, and R. Singh, R., (2018). Computer-aided Diagnosis for Characterising Colorectal Lesions: Interim Results of a Newly Developed Software. Gastrointestinal Endoscopy, 87(6), 2018.
- L.Z.C.T. Pu, K. Lu, A. Ovenden, S. Edwards, B. Wilson, G. Carneiro, A.D. Burt, and R. Singh (2018). Effect of Training and Time of the Day on Polyp Detection Rates in Australia. Gastrointestinal Endoscopy, 87(6), 2018.
2017
- Gustavo Carneiro, Jacinto C. Nascimento and Andrew Bradley. Automated Analysis of Unregistered Multi-view Mammograms with Deep Learning. IEEE Transactions on Medical Imaging (TMI) 36.11 (2017): 2355-2365. [pdf]
- Jacinto C.Nascimento and Gustavo Carneiro. Deep Learning on Sparse Manifolds for Faster Object Segmentation. IEEE Transactions on Image Processing (TIP) 26.10 (2017): 4978-4990. [pdf]
- Luke Oakden-Rayner, Gustavo Carneiro, Taryn Bessen, Jacinto Nascimento, Andrew Peter Bradley, Lyle Palmer. Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework. Scientific Reports 7.1 (2017): 1648. [link]
- Zhibin Liao, Gustavo Carneiro. A Deep Convolutional Neural Network Module that Promotes Competition of Multiple-size Filters. Pattern Recognition 71 (2017): 94-105. [pdf].
- Gustavo Carneiro, Tingying Peng, Christine Bayer, and Nassir Navab. Automatic Quantification of Tumour Hypoxia from Multi-modal Microscopy Images using Weakly-Supervised Learning Methods. IEEE Transactions on Medical Imaging. 36.7 (2017): 1405-1417. [pdf]
- Tuan Anh Ngo, Zhi Lu and Gustavo Carneiro. Combining Deep Learning and Level Set for the Automated Segmentation of the Left Ventricle of the Heart from Cardiac Cine Magnetic Resonance. Medical Image Analysis 35 (2017): 159-171. [pdf]
- Neeraj Dhungel, Gustavo Carneiro, Andrew Bradley. A Deep Learning Approach for the Analysis of Masses in Mammograms with Minimal User Intervention. Medical Image Analysis 37 (2017): 114-128. [pdf]
- Toan Minh Tran, Trung Thanh Pham, Gustavo Carneiro, Lyle Palmer, Ian Reid. A Bayesian Data Augmentation Approach for Learning Deep Models. Neural Information Processing Systems (NIPS). 2017. [pdf]
- Ben Harwood, Vijay Kumar B G, Gustavo Carneiro, Ian Reid, Tom Drummond. Smart Mining for Deep Metric Learning. International Conference on Computer Vision (ICCV 2017). [pdf]
- Gabriel Maicas, Gustavo Carneiro, Jacinto Nascimento, Andrew Bradley, Ian Reid. Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2017) [pdf]
- Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, A. P. Bradley. Mass Segmentation in Mammograms: a Cross-sensor Comparison of Deep and Tailored Features. International Conference on Image Processing (ICIP 2017) [pdf]
- Le Lu, Y. Zheng, G. Carneiro, L. Yang (Editors). Deep Learning and Convolutional Neural Networks for Medical Image Computing. Springer 2017 (ISBN 978-3-319-42999-1). [link]
- Tuan Anh Ngo and Gustavo Carneiro. Fully automated Segmentation using Distance Regularized Level Set and Deep-structured Learning and Inference. Book chapter in Deep Learning and Convolutional Neural Networks for Medical Image Computing. Springer 2017 (ISBN 978-3-319-42999-1). [link]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms. Book chapter in Deep Learning and Convolutional Neural Networks for Medical Image Computing. Springer 2017 (ISBN 978-3-319-42999-1). [link]
- Gustavo Carneiro, Jacinto Nascimento and Andrew Bradley. Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-view Images and Segmentation Maps of Lesions. Book chapter in Deep Learning for Medical Image Analysis. Elsevier/Academic Press 2017 (ISBN 9780128104088). [link]
- Adrian Johnston, Ravi Garg, Gustavo Carneiro, Ian Reid and Anton van den Hengel. Scaling CNNs for High Resolution Volumetric Reconstruction from a Single Image. ICCV 2017 Workshop: Geometry Meets Deep Learning. 2017. [pdf]
- Jerome Williams, Gustavo Carneiro, David Suter. Region of Interest Autoencoders.International Conference on Digital Image Computing: Techniques and Applications (DICTA). 2017. [pdf]
- David Ribeiro, Gustavo Carneiro, Jacinto C. Nascimento, Alexandre Bernardino. Multi-channel Convolutional Neural Network Ensemble for Pedestrian Detection. Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) 2017. [pdf]
- Gustavo Carneiro, Luke Oakden-Rayner, Andrew Peter Bradley, Jacinto Nascimento, Lyle Palmer. Automated 5-Year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography. International Symposium on Biomedical Imaging (ISBI) 2017. [pdf]
- Gabriel Maicas Suso, Gustavo Carneiro, Andrew Peter Bradley. Globally Optimal Breast Mass Segmentation from DCE-MRI Using Deep Semantic Segmentation As Shape Prior. International Symposium on Biomedical Imaging (ISBI) 2017. [pdf]
- Neeraj Dhungel, Gustavo Carneiro, Andrew Peter Bradley. Fully Automated Classification of Mammograms Using Deep Residual Neural Networks. International Symposium on Biomedical Imaging (ISBI) 2017. [pdf]
- Leonardo Pu,B. Campbell, G. Carneiro, A. Burt, R. Singh. Computer-aided diagnosis (CAD) for characterizing colorectal lesions: Initial results of newly developed software. Journal of Gastroenterology and Hepatology 32 pp 34-35.
2016
- David Ribeiro, Jacinto Nascimento, Alexandre Bernardino and Gustavo Carneiro. Improving the performance of pedestrian detectors using convolutional learning. Paper accepted for publication by Pattern Recognition in May/2016. [pdf]
- Fernanda A. Andalo, Gustavo Carneiro, Gabriel Taubin, Siome Goldenstein, Luiz Velho. Automatic reconstruction of ancient Portuguese tile panels. Paper accepted for publication by IEEE Computer Graphics and Applications in July/2016. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016) [pdf]
- Ravi Garg, Vijay Kumar B G, Gustavo Carneiro, Ian Reid. Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue. European Conference on Computer Vision (ECCV 2016) [pdf]
- Z. Lu, G. Carneiro, A. Bradley, D. Ushizima, M. S. Nosrati, A. Bianchi, C. Carneiro, and G. Hamarneh. "Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells." IEEE Journal of Biomedical and Health Informatics (2016) [pdf]
- Jacinto Nascimento and Gustavo Carneiro. Tracking and Segmentation of the Endocardium of the Left Ventricle in 2D Ultrasound using Deep Learning Architectures and Monte Carlo Sampling. Book Chapter in Biomedical Image Segmentation: Advances and Trends. Editors: Ayman El-Baz, Xiaoyi Jiang, Jasjit S. Suri. CRC Press, ISBN 9781482258554, 2016. [link]
- Gustavo Carneiro, Diana Mateus, Peter Loïc, Andrew Bradley, João Manuel Tavares, Vasileios Belagiannis, João Paulo Papa et al., eds. Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Vol. 10008. Springer, 2016. [link]
- Joao Paulo Costeira, Gustavo Carneiro, and Alessio Del Bue. Proceedings of the Workshop “VISART III – Where Computer Vision Meets Art”. Workshop held in conjunction with the 2016 European Conference on Computer Vision (ECCV). Amsterdam, The Netherlands, 2016.
- Vijay Kumar, Gustavo Carneiro and Ian Reid. "Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions." Computer Vision and Pattern Recognition (CVPR 2016) [pdf]
- Jacinto Nascimento and Gustavo Carneiro. "Multi-Atlas Segmentation Using Manifold Learning with Deep Belief Networks." IEEE International Symposium on Biomedical Imaging (ISBI 2016) [pdf]
- Zhibin Liao and Gustavo Carneiro. "On the Importance of Normalisation Layers in Deep Learning with Piecewise Linear Activation Units." IEEE Winter Conference on Applications of Computer Vision (WACV 2016) [pdf]
- H. Lee, A. Weerasinghe, J. Barnes, L. Oakden-Rayner, W. Gale and G. Carneiro. "CRISTAL: Adapting Workplace Training to the Real World Context with an Intelligent Simulator for Radiology Trainees." International Conference on Intelligent Tutoring Systems (ITS 2016) [pdf]
2015
- Zhi Lu, Gustavo Carneiro, and Andrew P. Bradley. "An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells." Image Processing, IEEE Transactions on 24, no. 4 (2015): 1261-1272. [pdf]
- Gustavo Carneiro, Tingying Peng, Christine Bayer, and Nassir Navab. "Weakly-Supervised Structured Output Learning With Flexible and Latent Graphs Using High-Order Loss Functions." In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2015. [pdf][dataset]
- Vasileios Belagiannis, Christian Rupprecht, Gustavo Carneiro, and Nassir Navab. "Robust Optimization for Deep Regression." In Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2015. [pdf]
- Gustavo Carneiro, Jacinto Nascimento and Andrew Bradley. Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models. In Proceedings of the Medical Image Computing and Computer Assisted Intervention (MICCAI) 2015. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms. In Proceedings of the Medical Image Computing and Computer Assisted Intervention (MICCAI) 2015. [pdf]
- Gustavo Carneiro, Tingying Peng, Christine Bayer and Nassir Navab. Flexible and Latent Structured Output Learning: Application to Histology. In MICCAI Workshop Machine Learning in Medical Imaging (MLMI) 2015. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Automated Mass Detection from Mammograms using Deep Learning and Random Forest. In MICCAI Workshop Breast Image Analysis (BIA) 2015. [pdf]
- Gustavo Carneiro, Tingying Peng, Christine Bayer and Nassir Navab. Automatic Detection of Necrosis, Normoxia and Hypoxia in Tumors from Multimodal Cytological Images. In Proceedings of the International Conference on Image Processing (ICIP) 2015. [pdf] Paper selected among the top 10% of the accepted papers of the conference!
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Deep Structured Learning for Mass Segmentation from Mammograms. In Proceedings of the International Conference on Image Processing (ICIP) 2015. [pdf] Paper selected among the top 10% of the accepted papers of the conference!
- Tuan Anh Ngo and Gustavo Carneiro. Lung Segmentation in Chest Radiographs using Distance Regularized Level Set and Deep-structured Learning and Inference. In Proceedings of the International Conference on Image Processing (ICIP) 2015. [pdf]
- Zhibin Liao and Gustavo Carneiro. The use of Deep Learning Features in a Hierarchical Classifier Learned with the Minimization of a Non-greedy Loss Function that Delays Gratification. In Proceedings of the International Conference on Image Processing (ICIP) 2015. [pdf]
- Jacinto Nascimento and Gustavo Carneiro. Towards reduction of the training and search running time complexities for non-rigid object segmentation. In Proceedings of the International Conference on Image Processing (ICIP) 2015. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Tree Re-Weighted Belief Propagation Using Deep Learning Potentials for Mass Segmentation from Mammograms. In Proceedings of the International Symposium on Biomedical Imaging (ISBI) 2015. [pdf]
- Adrian Johnston, Gustavo Carneiro, Ren Ding and Luiz Velho. 3-D Modeling from Concept Sketches of Human Characters with Minimal User Interaction. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2015. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Automated Mass Detection from Mammograms using Cascaded Deep Learning and Random Forests. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA) 2015. [pdf]
2014
- Joao Paulo Costeira, Gustavo Carneiro, and Alessio Del Bue. Proceedings of the Workshop “VISART III – Where Computer Vision Meets Art”. Workshop held in conjunction with the 2014 European Conference on Computer Vision (ECCV). Zurich, Switzerland, 2014.
- Tuan Anh Ngo and Gustavo Carneiro. Fully Automated Non-rigid Segmentation with Distance Regularized Level Set Evolution Initialized and Constrained by Deep-structured Inference. Computer Vision and Pattern Recognition (CVPR) 2014. [pdf]
- Jacinto Nascimento and Gustavo Carneiro. Non-rigid Segmentation using Sparse Low dimensional Manifolds and Deep Belief Networks. Computer Vision and Pattern Recognition (CVPR) 2014 [pdf]
- Qian Chen and Gustavo Carneiro. Artistic Image Analysis Using the Composition of Human Figures. European Conference on Computer Vision (ECCV) Workshops 2014. [pdf]
- Neeraj Dhungel, Gustavo Carneiro and Andrew Bradley. Deep Structured Learning for Mass Segmentation from Mammograms. Arxiv 2014. [pdf]
- Gustavo Carneiro and Duarte Lazaro. Book chapter in "Heranca de Santos Simoes - Novas Perspectivas para o Estudo da Azulejaria e da Ceramica". (Book in Portuguese) Ed. Colibri. 2014. [pdf]
2013
- Gustavo Carneiro, Fernando Amat, Bogdan Georgescu, Sara Good, and Dorin Comaniciu. Automated Fetal Measurements from Three-dimensional Ultrasound Data. US Patent number 8,556,814 B2. 2013. [pdf]
- Gustavo Carneiro and Jacinto Nascimento. Combining Multiple Dynamic Models and Deep Learning Architectures for Tracking the Left Ventricle Endocardium in Ultrasound Data. IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol.35, No.11, 2013. [pdf]
- Gustavo Carneiro. Artistic Image Analysis using Graph-based Learning Approaches. IEEE Transactions on Image Processing. Vol. 22, No. 8, 2013. [pdf]
- Joao Paulo Costeira, Gustavo Carneiro, and Alessio Del Bue. Proceedings of the Workshop “VISART I – Where Computer Vision Meets Art”. Workshop held in conjunction with the 2012 European Conference on Computer Vision (ECCV). Florence, Italy, 2012.
- Jacinto Nascimento and Gustavo Carneiro. Top-down Segmentation of Non-rigid Visual Objects using Derivative-based Search on Sparse Manifolds. Computer Vision and Pattern Recognition (CVPR) 2013. [pdf]
- Zhi Lu, Gustavo Carneiro and Andrew Bradley. Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells. In Proceedings of the Medical Image Computing and Computer Assisted Intervention (MICCAI) 2013. [Code and dataset are available from this link].[pdf]
- Jacinto Nascimento and Gustavo Carneiro. Combining a Bottom-up and Top-down Classifiers for the Segmentation of the Left Ventricle from Cardiac Imagery. International Conference on Image Processing (ICIP) 2013. [pdf]
- Tuan Anh Ngo and Gustavo Carneiro. Left Ventricle Segmentation from Cardiac MRI Combining Level Set Methods with Deep Belief Networks. International Conference on Image Processing (ICIP) 2013. [pdf] Paper selected among the top 10% of the accepted papers of the conference!
- Gustavo Carneiro, Zhibin Liao and Tat-Jun Chin. Closed-Loop Deep Vision. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA). 2013. [pdf]
- William Liu, Tat-Jun Chin, Gustavo Carneiro and David Suter. Point Correspondence Validation Under Unknown Radial Distortion. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA). 2013.
- F.A. Andalo, G. Carneiro, S. Goldenstein, G. Taubin and L. Velho. Image Puzzle Methods Applied to the Automatic Reconstruction of Ancient Portuguese Tile Panels. Technical Report - Instituto de Matematica Pura e Aplicada (IMPA). 2013. [pdf]
- Danilo Dell'Agnello, Gustavo Carneiro, Tat-Jun Chin, Giovanna Castellano and Anna Maria Fanelli. Fuzzy Clustering based Encoding for Visual Object Classification IFSA World Congress. NAFIPS Annual Meeting 2013.
2012
- Gustavo Carneiro, Jacinto Nascimento, Antonio Freitas. The Segmentation of the Left Ventricle of the Heart from Ultrasound Data using Deep Learning Architectures and Derivative-based Search Methods. IEEE Transactions on Image Processing. Vol. 21, No. 3. 2012. [pdf]
- Shaohua Kevin Zhou, Feng Guo, Jin-Hyeong Park, Gustavo Carneiro, Constantine Simpoulos, Joanne Otsuki, Dorin Comaniciu, and John Jackson. Method and System for Detection of Deformable Structures in Medical Images. US Patent number 8,150,116 B2. 2012.
- Gustavo Carneiro, Nuno Pinho da Silva, Alessio Del Bue, and Joao Paulo Costeira. Artistic Image Classification: an Analysis on the PRINTART Database. European Conference on Computer Vision (ECCV) 2012. [pdf] [dataset]
- Quoc-Huy Tran, Tat-Jun Chin, Gustavo Carneiro, Michael S. Brown, and David Suter. In Defence of RANSAC for Outlier Rejection in Deformable Registration. European Conference on Computer Vision (ECCV) 2012. [pdf]
- Gustavo Carneiro, Jacinto Nascimento. The Use of On-line Co-training to Reduce the Training Set Size in Pattern Recognition Methods: Application to Left Ventricle Segmentation in Ultrasound. Computer Vision and Pattern Recognition (CVPR) 2012. [pdf]
- Gustavo Carneiro, Jacinto Nascimento. On-line Re-training and Segmentation with Reduction of the Training Set: Application to the Left Ventricle Detection on Ultrasound Imaging. International Conference on Image Processing (ICIP) 2012. [pdf]
2011
- Gustavo Carneiro, Bogdan Georgescu, Sara Good, and Dorin Comaniciu. System and Method for Detection of Fetal Anatomies from Ultrasound Images using a Constrained Probabilistic Boosting Tree. US Patent number 7,995,820. 2011
- Gustavo Carneiro, Jacinto C. Nascimento: Incremental On-line Semi-supervised Learning for Segmenting the Left Ventricle of the Heart from Ultrasound Data. International Conference on Computer Vision (ICCV) 2011.[pdf]
- Jacinto C. Nascimento, Gustavo Carneiro: Reducing the Training Set Using Semi-Supervised Self-Training Algorithm for Segmenting the Left Ventricle in Ultrasound Images. International Conference on Image Processing (ICIP) 2011. [pdf]
- Gustavo Carneiro: Graph-based Methods for the Automatic Annotation and Retrieval of Art Prints. ACM International Conference on Multimedia Retrieval (ICMR) 2011.[pdf]
- Gustavo Carneiro, Jacinto C. Nascimento, António Freitas: Semi-supervised self-training model for the segmentationof the left ventricle of the heart from ultrasound data. IEEE International Symposium on Biomedical Imaging (ISBI) 2011.[pdf]
- Gustavo Carneiro, João P. Costeira: The automatic annotation and retrieval of digital images of prints and tile panels using network link analysis algorithms. Computer Vision and Image Analysis of Art II (Proceedings of SPIE Volume: 7869) 2011. [pdf]
- Nuno Pinho da Silva, Manuel Marques, Gustavo Carneiro, João P. Costeira: Explaining scene composition using kinematic chains of humans: application to Portuguese tiles history.Computer Vision and Image Analysis of Art II (Proceedings of SPIE Volume: 7869). 2011.
- Ricardo S. Cabral, João P. Costeira, Fernando de La Torre, Alexandre Bernardino, Gustavo Carneiro: Time and order estimation of paintings based on visual features and expert priors. Computer Vision and Image Analysis of Art II (Proceedings of SPIE Volume: 7869). 2011.
2010
- Gustavo Carneiro, Sara Good, Bogdan Georgescu, Paolo Favaro, and Dorin Comaniciu. System and Method for Fetal Biometric Measurements from Ultrasound Data and Fusion of same for Estimation of Fetal Gestational Age. US Patent number 7,783,095. 2010.
- Michael Wels, Gustavo Carneiro, Martin Huber, Dorin Comaniciu, Yefeng Zheng. Method and System for Segmentation of Brain Structures in 3D Magnetic Resonance Images. US Patent Application number 20100074499. 2010.
- Michael Wels, Gustavo Carneiro, Martin Huber, Dorin Comaniciu. Method and System for Brain Tumor Segmentation in 3D Magnetic Resonance Images. US Patent Application number 20100027865. 2010.
- Gustavo Carneiro: The automatic design of feature spaces for local image descriptors using an ensemble of non-linear feature extractors. Computer Vision and Pattern Recognition (CVPR) 2010: 3509-3516. [Matlab code for toy example].[pdf]
- Gustavo Carneiro, Jacinto C. Nascimento: Multiple dynamic models for tracking the left ventricle of the heart from ultrasound data using particle filters and deep learning architectures. Computer Vision and Pattern Recognition (CVPR) 2010: 2815-2822 . [pdf]
- Jacinto C. Nascimento, Gustavo Carneiro: Efficient search methods and deep belief networks with particle filtering for non-rigid tracking: Application to lip tracking. International Conference on IMage Processing (ICIP) 2010: 3817-3820 . [pdf]
- Gustavo Carneiro, Jacinto C. Nascimento: The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking. International Conference on Pattern Recognition (ICPR) 2010: 2065-2068. [pdf]
- Gustavo Carneiro: A Comparative Study on the Use of an Ensemble of Feature Extractors for the Automatic Design of Local Image Descriptors. International Conference on Pattern Recognition (ICPR) 2010: 3356-3359. [pdf]
- Gustavo Carneiro, Jacinto C. Nascimento, António Freitas: Robust left ventricle segmentation from ultrasound data using deep neural networks and efficient search methods. IEEE International Symposium on Biomedical Imaging (ISBI) 2010: 1085-1088. [pdf]
2009
- Gustavo Carneiro, Nuno Vasconcelos: Minimum Bayes error features for visual recognition. Image Vision Comput. 27(1-2): 131-140 (2009). [pdf]
- Gustavo Carneiro, Allan D. Jepson: The quantitative characterization of the distinctiveness and robustness of local image descriptors. Image Vision Comput. 27(8): 1143-1156 (2009). [pdf]
- I. Zalud, S. Good, Gustavo Carneiro, B. Georgescu, K. Aoki, L. Green, F. Shahrestani, R. Okumura. Fetal Biometry: A Comparison Between Experienced Sonographers and Automated Measurements, The Journal of Maternal-fetal and Neonatal Medicine, 2, 22(1):43-50, 2009.
- Dorin Comaniciu, Shaohua Kevin Zhou, Feng Guo, Jin-Hyeong Park, Gustavo Carneiro, Constantine Simpoulos, Joanne Otsuki, and John Jackson. Method and System for Detection of Deformable Structures in Medical Images. US Patent Application number 20090010509. 2009.
- Michael Wels, Yefeng Zheng, Gustavo Carneiro, Martin Huber, Joachim Hornegger, Dorin Comaniciu: Fast and Robust 3-D MRI Brain Structure Segmentation. MICCAI (1) 2009: 575-583 [pdf]
2008
- Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dorin Comaniciu: Detection and Measurement of Fetal Anatomies from Ultrasound Images using a Constrained Probabilistic Boosting Tree. IEEE Trans. Med. Imaging 27(9): 1342-1355 (2008).[pdf]
- Gustavo Carneiro, Fernando Amat, Bogdan Georgescu, Sara Good, Dorin Comaniciu: Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling. CVPR 2008. [pdf]
- Michael Wels, Gustavo Carneiro, Alexander Aplas, Martin Huber, Joachim Hornegger, Dorin Comaniciu: A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI. MICCAI (1) 2008: 67-75 . [pdf]
2007
- Gustavo Carneiro, Allan D. Jepson: Flexible Spatial Configuration of Local Image Features. IEEE Trans. Pattern Anal. Mach. Intell. 29(12): 2089-2104 (2007). [pdf]
- Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno, Nuno Vasconcelos: Supervised Learning of Semantic Classes for Image Annotation and Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 29(3): 394-410 (2007). [pdf]
- Shaohua Kevin Zhou, Feng Guo, Gustavo Carneiro, John Jackson, M. Brendel, Costas Simopoulos, Joanne Otsuki, Dorin Comaniciu: A probabilistic, hierarchical, and discriminant framework for rapid and accurate detection of deformable anatomic structure. ICCV 2007: 1-8 . [pdf]
- Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dorin Comaniciu: Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree. MICCAI (2) 2007: 571-579 . [pdf]
2006
- Manuela Vasconcelos, Nuno Vasconcelos, Gustavo Carneiro: Weakly Supervised Top-down Image Segmentation. CVPR (1) 2006: 1001-1006. [pdf]
- Gustavo Carneiro, David Lowe: Sparse Flexible Models of Local Features. ECCV (3) 2006: 29-43. [pdf]
2005
- Gustavo Carneiro, Nuno Vasconcelos: Formulating Semantic Image Annotation as a Supervised Learning Problem. CVPR (2) 2005: 163-168. [pdf]
- Gustavo Carneiro, Allan D. Jepson: The Distinctiveness, Detectability, and Robustness of Local Image Features. CVPR (2) 2005: 296-301. [pdf]
- Gustavo Carneiro, Nuno Vasconcelos: A database centric view of semantic image annotation and retrieval. ACM SIGIR 2005: 559-566. [pdf]
- Gustavo Carneiro, Nuno Vasconcelos: Minimum Bayes Error Features for Visual Recognition by Sequential Feature Selection and Extraction. CRV 2005: 253-260. [pdf]
2004
- Gustavo Carneiro. (2004). Image Representation Using Phase-based Local Image Descriptors and their Flexible Spatial Configuration. Ph.D. Thesis. University of Toronto. Department of Computer Science. [pdf]
- Gustavo Carneiro, Allan D. Jepson: Flexible Spatial Models for Grouping Local Image Features. CVPR (2) 2004: 747-754. [pdf]
- Gustavo Carneiro, Allan D. Jepson: Pruning Local Feature Correspondences Using Shape Context. ICPR (3) 2004: 16-19 . [pdf]
2003
- Gustavo Carneiro, Allan D. Jepson: Multi-scale Phase-based Local Features. CVPR (1) 2003: 736-743. [pdf]
2002
- Gustavo Carneiro, Allan D. Jepson: Phase-Based Local Features. ECCV (1) 2002: 282-296. [pdf]
- Nuno Vasconcelos, Gustavo Carneiro: What Is the Role of Independence for Visual Recognition? ECCV (1) 2002: 297-311. [pdf]
1999
- Eliana P. L. Aude, Gustavo Carneiro, Henrique Serdeira, Julio Silveira, Mario F. Martins, Ernesto P. Lopes: CONTROLAB MUFA: A Multi-Level Fusion Architecture for Intelligent Navigation of a Telerobot. ICRA 1999: 465-472. [pdf]
- Gustavo Carneiro, Eliana Aude, Henrique Serdeira, Julio Silveira, Mario Martins, Ernesto Lopes. An Internet Request Server Architecture for Telecommanding the CONTROLAB AGV through Real Time Data and Image. Proceedings of the 42nd Midwest Symposium on Circuits and Systems. Las Cruces, New Mexico. USA. 1999. [pdf]
- Eliana Aude, Gustavo Carneiro, Henrique Serdeira, Julio Silveira, Mario Martins, Ernesto Lopes. Integration of Intelligent Systems and Sensor Fusion within the CONTROLAB AGV.Proceedings of the SPIE Intenational Symposium on Intelligent Systems and Advanced Manufacturing. Program on Mobile Robots and Autonomous Systems. Boston, Massachusetts. 1999. [pdf]
- Gustavo Carneiro. (1999). Tratamento de Comandos Remotos e Processamento de Visao para Navegacao de Veiculos Autonomos em Tempo Real. MSc. Thesis. Military Institute of Engineering. [pdf]
1998
- Claudio G. Mello , Gustavo H. M. B. Carneiro , Paulo R. Lira Gondim: Setting Up A MBone Node For Distance Learning Purposes. ICEE 98. [pdf]