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 2010Ismail 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.
Télécharger le livre :  Less-Supervised Segmentation with CNNs

Less-Supervised Segmentation with CNNs: Scenarios, Models and Optimization reviews recent progress in deep learning for image segmentation under scenarios with limited supervision, with a focus on medical imaging. The book presents main approaches and state-of-the-art...
Editeur : Academic Press
Parution : 2025-08-29

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Télécharger le livre :  High-Order Models in Semantic Image Segmentation

High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful...
Editeur : Academic Press
Parution : 2023-06-22

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