Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition) 1st Edition by E. R. Davies 9780128221495 0128221496

Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition) 1st Edition E. R. Davies – Ebook Instant Download/Delivery ISBN(s): 9780128221099, 0128221097, 9780128221495, 0128221496

Product details:

• ISBN 10: 0128221496
• ISBN 13: 9780128221495
• Author: E. R. Davies

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. 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, image inpainting, novelty and 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.

Table contents:

Chapter 1: The dramatically changing face of computer vision

Chapter 2: Advanced methods for robust object detection

Chapter 3: Learning with limited supervision

Chapter 4: Efficient methods for deep learning

Chapter 5: Deep conditional image generation

Chapter 6: Deep face recognition using full and partial face images

Chapter 7: Unsupervised domain adaptation using shallow and deep representations

Chapter 8: Domain adaptation and continual learning in semantic segmentation

Chapter 9: Visual tracking

Chapter 10: Long-term deep object tracking

Chapter 11: Learning for action-based scene understanding

Chapter 12: Self-supervised temporal event segmentation inspired by cognitive theories

Chapter 13: Probabilistic anomaly detection methods using learned models from time-series data for multimedia self-aware systems

Chapter 14: Deep plug-and-play and deep unfolding methods for image restoration

Chapter 15: Visual adversarial attacks and defenses

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