Deep Convolutional Neural Networks for Unconstrained Ear Recognition

Deep Convolutional Neural Networks for Unconstrained Ear Recognition

This paper employs state-of-the-art Deep Convolutional Neural Networks (CNNs), namely AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear recognition on the unconstrained EarVN1.0 dataset. As the dataset size is still insufficient to train deep CNNs from scratch, we u...

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Bibliographic Details
Main Authors: Hammam Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Ear recognition
biometrics
deep learning
convolutional neural networks
transfer learning
feature visualization
Online Access:https://ieeexplore.ieee.org/document/9195824/

Internet

https://ieeexplore.ieee.org/document/9195824/

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