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Book on Advanced Methods and Deep Learning in Computer Vision

This book was edited by E.R Davies and Matthew Turk and published by Elsevier, Academic Press on 12 November 2021. It carries a wealth of detail on vision algorithms developed since the Deep Learning explosion of 2012, and will be of immense value to researchers and practitioners of the subject.

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine learning and deep learning techniques that have emerged during the past 5–10 years. It provides clear explanations of principles and algorithms and aims to give new insights into the underlying theory of advanced vision algorithms. Topics covered include:

machine learning
deep learning networks
generative adversarial networks
deep reinforcement learning
self-supervised learning
extraction of robust features
object detection, semantic segmentation
linguistic descriptions of images
visual search
visual tracking
3D shape retrieval
anomaly detection.

This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students.

See full list of contents for further details.