Deep Learning in Biometrics

Mayank Vatsa

ISBN 10: 1032653108 / ISBN 13: 9781032653105

Editore: Taylor & Francis Ltd Okt 2023, 2023

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Neuware - This book will cover all the topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoenders. The focus will be on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints.

Codice articolo 9781032653105

Dati bibliografici

• Titolo: Deep Learning in Biometrics
• Editore: Taylor & Francis Ltd Okt 2023
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 1032653108
• ISBN 13: 9781032653105
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 234 L x 156 A x 0 P (millimetri) 234 millimetri di larghezza per 156 millimetri di altezza per 0 millimetri di profondità
• Peso: 580 grammi

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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.