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Advances in Deep Learning
Kategorie	Beschreibung
036a	XB-SG
037b	eng
087q	978-981-13-6793-9
100	Wani, M. Arif ¬[VerfasserIn]¬
104a	Bhat, Farooq Ahmad ¬[VerfasserIn]¬
108a	Afzal, Saduf ¬[VerfasserIn]¬
112a	Khan, Asif Iqbal ¬[VerfasserIn]¬
331	Advances in Deep Learning
410	Singapore
412	Springer
425	2020
425a	2020
433	1 Online-Ressource (XIV, 149 p. 87 illus., 53 illus. in color)
451	Studies in Big Data ; 57
527	Erscheint auch als (Druck-Ausgabe)ISBN: 978-981-13-6793-9
540a	ISBN 978-981-13-6794-6
700	\|COM004000
700	\|UYQ
700	\|*68-02
700	\|68T05
700	\|68T10
700	\|UYQ
700	\|TEC009000
700b	\|006.3
700c	\|Q342
750	Preface -- Introduction to Deep Learning -- Basic Deep Learning Models -- Training Basic Deep Learning Models -- Optimising Deep Learning Models -- Application of Deep Learning in Classification -- Application of Deep Learning in Segmentation -- Application of Deep Learning in Face Recognition -- Application of Deep Learning in Fingerprint Recognition -- Author's Index
753	This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models
012	1666746088
081	Advances in Deep Learning
100	Springer E-Book
125a	Elektronischer Volltext - Campuslizenz
655e	$uhttps://doi.org/10.1007/978-981-13-6794-6