Deep Learning in Visual Computing Explanations and Examples / Hassan Ugail Director, Centre for Visual Computing University of Bradford Bradford, UK.

Author/creator Ugail, H.
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press ; Taylor and Francis Group, 2022.
Description1 online resource (131 pages)
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents The foundations of deep learning -- Deep learning models for visual computing -- Deep face recognition -- Age estimation from face images using deep learning -- The nose and ethnicity -- Analysis of skin burns using deep learning -- Deep learning approaches to cancer diagnosis using histopathological images -- A deep transfer learning model for the analysis of electrocardiograms -- Advances in visual computing through deep learning -- Frontiers and challenges in deep learning for visual computing.
Abstract "This book provides a unique insight into the explosive area of deep machine learning and how the challenges in visual computing can be tackled through this novel method of machine learning. The book introduces the reader to the world of deep neural network architectures with easy to understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find this book as a handy guide for designing and implementing their own projects in the field of visual computing"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher; resource not viewed.
Issued in other formPrint version: Deep Learning in Visual Computing Boca Raton : CRC Press ; 2022. 9780367549626
Genre/formElectronic books.
LCCN 2023701966
ISBN9781000625455 ebook
ISBN(hardcover)
ISBN(paperback)

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