High-Order Models in Semantic Image Segmentation - Rilegato

Ben Ayed

Rilegato

ISBN 10: 0128053208 ISBN 13: 9780128053201

Casa editrice: Academic Press, 2023

Riassunto

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 algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging.

Su questo libro

Informazioni sull'autore

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.

Dalla quarta di copertina

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 algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. This book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging

Dettagli dell'edizione

• Editore: Academic Press
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 0128053208
• ISBN 13: 9780128053201
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 182
• Contatto del produttore: Academic Press; https://shop.elsevier.com/; ; 230 PARK AVENUE, SUITE 800; NY; NY; 10169; U.S.A.
• Persona responsabile: non disponibile