Less-Supervised Segmentation with CNNs

Jose Dolz is an Associate Professor in the Department of Software and IT Engineering at the ETS Montreal. Prior to be appointed Professor, he was a post-doctoral fellow at the ETS Montreal. Dr. Dolz obtained his B.Sc and M.Sc in the Polytechnic University of Valencia, Spain, and his Ph.D. at the University of Lille 2, France, in 2016. Dr. Dolz was recipient of a Marie-Curie FP7 Fellowship (2013-2016) to pursue his doctoral studies. His current research focuses on deep learning, medical imaging, optimization and learning strategies with limited supervision. He authored over 30 fully peer-reviewed papers, many of which published in the top venues in medical imaging (MICCAI/IPMI/MedIA/TMI/NeuroImage), vision (CVPR) and machine learning (ICML, NeurIPS). Ismail Ben Ayed received a Ph.D. degree (with the highest honor) in the area of computer vision from the National Institute of Scientific Research (INRS-EMT), University of Quebec, Montreal, QC, Canada, in May 2007, under the guidance of Professor Amar Mitiche. Since then, he has been a research scientist with GE Healthcare, London, ON, Canada, conducting research in medical image analysis. He also holds an Adjunct Professor appointment at Western University, department of Medical Biophysics. He co-authored a book, over 50 peer-reviewed papers in reputable journals and conferences, and six patents. He received a GE recognition award in 2012 and a GE innovation award in 2010 Ismail Ben Ayed is an image segmentation and optimization expert who has authored over 60 peer-reviewed articles in the field and has co-authored the book Variational and Level Set Methods in Image Segmentation, 2011, which is receiving a high citation rate. Christian Desrosiers, Since 2009 Christian Desrosiers has worked as an assistant professor in the Software and IT Engineering department at ÉTS, Montreal. Before joining the department, he was a postdoctoral research assistant at the University of Minnesota, under the supervision of professor George Karypis. He obtained my Ph.D. in applied mathematics at École Polytechnique de Montréal, in 2008. His main areas of research are data mining, machine learning, biomedical imaging, recommender systems and business intelligence.

1. Introduction
2. Preliminaries
3. Different levels of supervision
4. Semi-supervised learning
5. Unsupervised domain adaptation
6. Weakly supervised segmentation
7. Few-shot learning
8. Unsupervised segmentation
9. Perspectives and future directions