finelybook
Deep Learning in Computer Vision: Principles and Applications (Digital Imaging and Computer Vision)
by 作者: Mahmoud Hassaballah and Ali Ismail Awad
Series: Digital Imaging and Computer Vision
Pages: 338 pages
Publisher Finelybook 出版社: CRC Press; 1 edition (April 13,2020)
Language 语言: English
ISBN-10 书号: 1138544426
ISBN-13 书号: 9781138544420
Book Description
Deep learning algorithms have brought a revolution to the computer vision community by 作者: 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
Foreword
Preface
Editors Bio
Contributors
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 4A 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 lmaging
Chapter 10 Lossless Full-Resolution Deep Learning Convolutional
Networks for Skin Lesion Boundary Segmentation
Chapter 11 Skin Melanoma Classification Using Deep Convolutional
Neural Networks
Index
