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CRC Press
12 March 2018
Automatic control engineering; Machine learning; Image processing
Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research.

Contains chapters written by authors who are leading researchers in biometrics.

Presents a comprehensive overview on the internal mechanisms of deep learning.

Discusses the latest developments in biometric research.

Examines future trends in deep learning and biometric research.

Provides extensive references at the end of each chapter to enhance further study.
Edited by:   Mayank Vatsa (IIIT Delhi India), Richa Singh (IIIT Delhi, India), Angshul Majumdar (Indraprastha Institute of Information Technology, Delhi, India)
Imprint:   CRC Press
Country of Publication:   United Kingdom
Dimensions:   Height: 235mm,  Width: 156mm, 
Weight:   590g
ISBN:   9781138578234
ISBN 10:   1138578231
Pages:   316
Publication Date:   12 March 2018
Audience:   College/higher education ,  Primary
Format:   Hardback
Publisher's Status:   Active

Mayank Vatsa is an Associate Professor at IIIT New Delhi. He has authored more than 150 publications dealing with biometrics, image processing, machine learning and information fusion. He is a Senior Member of IEEE. Richa Singh is an Associate Professor at IIIT New Delhi. She has authored over 100 publications on biometrics, patter recognition and machine learning in referred journals, book chapters and conferences. Angshul Majumdar is an Assistant Professor at IIIT New Delhi. He is an active research in biomimetics and machine learning.

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