TUM Library catalog › Details for: AI and deep learning in biometric security : trends, potential, and challenges /

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AI and deep learning in biometric security : trends, potential, and challenges / edited by Gaurav Jaswal, Vivek Kanhangad, and Raghavendra Ramachandra.

Contributor(s): Jaswal, Gaurav [editor.] | Kanhangad, Vivek [editor.] | Ramachandra, Raghavendra [editor.]Material type: Text

TextSeries: Artificial intelligence (AI) : elementary to advanced practicesPublisher: Boca Raton, FL : CRC Press, 2021Edition: First editionDescription: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781003003489; 1003003486; 9781000291667; 1000291669; 9781000291629; 1000291626; 9781000291643; 1000291642Subject(s): Biometric identification | Artificial intelligence | COMPUTERS / Machine Theory | TECHNOLOGY / Manufacturing | COMPUTERS / Programming / Systems Analysis & DesignDDC classification: 006.2/48 LOC classification: TK7882.B56Online resources: Taylor & Francis | OCLC metadata license agreement

Partial contents:

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.

Summary: "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"-- Provided by publisher.

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"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"-- Provided by publisher.

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