Advances in Deep Learning

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Synopsis

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.

Book details

Edition:
1st ed. 2020
Series:
Studies in Big Data (Book 57)
Author:
M. Arif Wani, Farooq Ahmad Bhat, Saduf Afzal, Asif Iqbal Khan
ISBN:
9789811367946
Related ISBNs:
9789811367939
Publisher:
Springer Singapore, Singapore
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-03-21
Usage restrictions:
Copyright
Copyright date:
2020
Copyright by:
Springer Nature Singapore Pte Ltd. 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Mathematics and Statistics, Nonfiction