Deep Learning in Computer Vision (eBook, ePUB)

Principles and Applications
Redaktion: Hassaballah, Mahmoud; Awad, Ali Ismail

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 338
• Erscheinungstermin: 23. März 2020
• Englisch
• ISBN-13: 9781351003803
• Artikelnr.: 58879393

Autorenporträt

Mahmoud Hassaballah received the Doctor of Engineering (D. Eng.) in Computer Science from Ehime University, Japan in 2011. He was a visiting scholar with the Department of Computer & Communication Science, Wakayama University, Japan and GREAH laboratory, Le Havre Normandie University, France. He is currently an Associate Professor of Computer Science at the Faculty of Computers and Information, South Valley University, Egypt. His research interests include feature extraction, object detection/recognition, artificial intelligence, biometrics, image processing, computer vision, machine learning, and data hiding. Ali Ismail Awad is currently an Associate Professor (Docent) with the Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden, where he also serves as a Coordinator of the Master Programme in Information Security. He is a Visiting Researcher with the University of Plymouth, United Kingdom. He is also an Associate Professor with the Electrical Engineering Department, Faculty of Engineering, Al-Azhar University at Qena, Qena, Egypt. His research interests include information security, Internet-of-Things security, image analysis with applications in biometrics and medical imaging, and network security.

Inhaltsangabe

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