Group sparse autoencoder

Unsupervised feature extraction is gaining a lot of research attention following its success to represent any kind of noisy data. Owing to the presence of a lot of training parameters, these feature learning models are prone to overfitting. Different regularization methods have been explored in the...

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Bibliographic Details

Published in:	Image and vision computing Vol. 60; pp. 64 - 74
Main Authors:	Sankaran, Anush, Vatsa, Mayank, Singh, Richa, Majumdar, Angshul
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.04.2017
Subjects:	Group sparsity Latent fingerprint Minutia extraction Supervised autoencoder Group sparsity Latent fingerprint Supervised autoencoder Minutia extraction
ISSN:	0262-8856, 1872-8138
Online Access:	Get full text
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