Learning Biometric Representations with Mutually Independent Features Using Convolutional Autoencoders

Representations of biometric traits to be used in automatic recognition systems are typically learned with the goal of obtaining significant discriminative capabilities, that is, generating features that are notably different when produced by traits of different subjects, while maintaining an approp...

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Vydané v:	SN computer science Ročník 4; číslo 5; s. 619
Hlavní autori:	Musto, Riccardo, Kuzu, Ridvan Salih, Maiorana, Emanuele, Hine, Gabriel Emile, Campisi, Patrizio
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Singapore Springer Nature Singapore 01.09.2023 Springer Nature B.V
Predmet:	Access control Advances on Pattern Recognition Applications and Methods 2022 Biometric recognition systems Biometrics Coefficients Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data integrity Data Structures and Information Theory Fingers Information Systems and Communication Service Learning Original Research Pattern Recognition and Graphics Performance evaluation Representations Software Engineering/Programming and Operating Systems Veins Vision Representation learning Biometric recognition Statistical independence Vein patterns
ISSN:	2661-8907, 2662-995X, 2661-8907
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