Deep learning in computer vision : principles and applications
Author(s)
Bibliographic Information
Deep learning in computer vision : principles and applications
（Digital imaging and computer vision series）
CRC Press, c2020
- : hardback
Available at 3 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.
Table of Contents
Chapter 1 Accelerating the CNN Inference on FPGAs Chapter 2 Object Detection with Convolutional Neural Networks Chapter 3 Efficient Convolutional Neural Networks for Fire Detection in Surveillance Applications Chapter 4 A Multi-biometric Face Recognition System Based on Multimodal Deep Learning Representations Chapter 5 Deep LSTM-Based Sequence Learning Approaches for Action and Activity Recognition Chapter 6 Deep Semantic Segmentation in Autonomous Driving Chapter 7 Aerial Imagery Registration Using Deep Learning for UAV Geolocalization Chapter 8 Applications of Deep Learning in Robot Vision Chapter 9 Deep Convolutional Neural Networks: Foundations and Applications in Medical Imaging Chapter 10 Lossless Full-Resolution Deep Learning Convolutional Networks for Skin Lesion Boundary Segmentation Chapter 11 Skin Melanoma Classification Using Deep Convolutional Neural Networks
by "Nielsen BookData"