Advances in deep learning / M. Arif Wani, Farooq Ahmad Bhat, Saduf Afzal, Asif Iqbal Khan.
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 compo...
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| Main Authors: | , , , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Singapore :
Springer,
[2020]
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| Series: | Studies in big data ;
v. 57. |
| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | 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. |
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| Physical Description: | 1 online resource (xiv, 149 pages). |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 9811367930 9789811367939 9811367949 9789811367946 |