A Guide to Convolutional Neural Networks for Computer Vision

A Guide to Convolutional Neural Networks for Computer Vision offers a comprehensive introduction to the theory and practice of convolutional neural networks (CNNs) in the field of computer vision. This specialized book is aimed at readers who want to understand both the fundamental concepts and practical applications of CNNs. It covers essential topics such as training, regularization, and optimization of CNNs. Additionally, various loss functions, network architectures, and evaluation techniques are presented. The authors, Salman Khan, Mohammed Bennamoun, Hossein Rahmani, and Syed Afaq Ali Shah, also provide insights into common tools and libraries used in computer vision. By discussing case studies on topics such as image classification, object detection, and semantic segmentation, the book deepens the understanding of the application of CNNs in real-world scenarios. This book is a valuable resource for students, professionals, and anyone interested in the latest developments in computer vision.