2024-03-29T11:04:20Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1342522024-03-13T09:52:52Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
2017-09-05T10:58:59Z
urn:hdl:10366/134252
A Brief Review of the Ear Recognition Process using Deep Neural Networks
Galdámez, Pedro L.
Raveane, William
González Arrieta, María Angélica
Computer Science
The process of precisely recognize people by ears has been getting major attention in recent years. It represents an important step in the biometric research, especially as a complement to face recognition systems which have difficult in real conditions. This is due to the great variation in shapes, variable lighting conditions, and the changing profile shape which is a planar representation of a complex object. An ear recognition system involving a convolutional neural networks (CNN) is proposed to identify a person given an input image. The proposed method matches the performance of other traditional approaches when analyzed against clean photographs. However, the F1 metric of the results shows improvements in specificity of the recognition. We also present a technique for improving the speed of a CNN applied to large input images through the optimization of the sliding window approach
2017-09-05T10:58:59Z
2017-09-05T10:58:59Z
2016
info:eu-repo/semantics/article
Journal of Applied Logic.
1570-8683
http://hdl.handle.net/10366/134252
en
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 Unported