High-Order Models in Semantic Image Segmentation
Published on 29. June 2023
Book
Hardback
250 pages
978-0-12-805320-1 (ISBN)
Description
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.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Computer scientists, electronic and biomedical engineers researching in computer vision, medical imaging, machine learning; graduate students in these fields.
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 234 mm
Width: 152 mm
Thickness: 15 mm
Weight
440 gr
ISBN-13
978-0-12-805320-1 (9780128053201)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Ismail Ben Ayed
High-Order Models in Semantic Image Segmentation
E-Book
06/2023
Academic Press
€95.95
Available for download
Person
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.
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.
Content
1. Introductory Background
2. Basic segmentation models
3. Standard optimization techniques
4. High-order models
5. Advanced optimization: Auxiliary functions and pseudo bounds
6. Advanced optimization: Trust region
7. Medical imaging applications
8. Appendix
2. Basic segmentation models
3. Standard optimization techniques
4. High-order models
5. Advanced optimization: Auxiliary functions and pseudo bounds
6. Advanced optimization: Trust region
7. Medical imaging applications
8. Appendix