Improving the Efficiency of Automated Latent Fingerprint Identification Using Stack of Convolutional Auto-encoder

In this paper, a method for improving the efficiency of latent fingerprint segmentation and detection system is presented. Structural detection and precise segmentation of fingerprints otherwise not visible to the naked eye (called latents), provide the basis for automatic identification of latent f...

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Vydané v:	International Conference on Parallel, Distributed and Grid Computing (PDGC ...) s. 191 - 196
Hlavní autori:	Chhabra, Megha, Shukla, Manoj Kumar, Ravulakollu, Kiran Kumar
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 06.11.2020
Predmet:	Autoencoder Convolutional neural network Classification Computational modeling Feature extraction Fingerprint recognition Image color analysis Image processing Image segmentation Latent fingerprint Load modeling Segmentation Training
ISSN:	2573-3079
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