AI and deep learning in biometric security : trends, potential, and challenges /

"This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. Thi...

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Bibliographic Details
Other Authors: Jaswal, Gaurav (Editor), Kanhangad, Vivek (Editor), Ramachandra, Raghavendra (Editor)
Format: Electronic eBook
Language:English
Published: Boca Raton, FL : CRC Press, 2021.
Edition:First edition.
Series:Artificial intelligence (AI) : elementary to advanced practices
Subjects:
Online Access:Taylor & Francis
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245 0 0 |a AI and deep learning in biometric security :  |b trends, potential, and challenges /  |c edited by Gaurav Jaswal, Vivek Kanhangad, and Raghavendra Ramachandra. 
250 |a First edition. 
264 1 |a Boca Raton, FL :  |b CRC Press,  |c 2021. 
300 |a 1 online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b n  |2 rdamedia 
338 |a online resource  |b nc  |2 rdacarrier 
490 0 |a Artificial intelligence (AI) : elementary to advanced practices 
505 2 |a Deep learning based hyperspectral multimodal biometric authentication system using palmprint and dorsal hand vein / Shuping Zhao, Wei Nie, Bob Zhang -- Cancelable biometrics for template protection: Future directives with deep learning / Avantika Singh, Gaurav Jaswal, Aditya Nigam -- On training generative adversarial network for enhancement of latent fingerprints / Indu Joshi, Adithya Anand, Sumantra D Roy and Prem K Kalra. 
520 |a "This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security"--  |c Provided by publisher. 
588 |a OCLC-licensed vendor bibliographic record. 
650 0 |a Biometric identification.  |9 43260 
650 0 |a Artificial intelligence.  |9 43261 
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650 7 |a COMPUTERS / Programming / Systems Analysis & Design  |2 bisacsh  |9 43264 
700 1 |a Jaswal, Gaurav,  |e editor.  |9 43265 
700 1 |a Kanhangad, Vivek,  |e editor.  |9 43266 
700 1 |a Ramachandra, Raghavendra,  |e editor.  |9 43267 
856 4 0 |3 Taylor & Francis  |u https://www.taylorfrancis.com/books/9781003003489 
856 4 2 |3 OCLC metadata license agreement  |u http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf 
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