Using Non-Additive Entropy to Enhance Convolutional Neural Features for Texture Recognition

Using Non-Additive Entropy to Enhance Convolutional Neural Features for Texture Recognition

Here we present a study on the use of non-additive entropy to improve the performance of convolutional neural networks for texture description. More precisely, we introduce the use of a local transform that associates each pixel with a measure of local entropy and use such alternative representation...

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Bibliographic Details
Main Authors: Joao Florindo, Konradin Metze
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Entropy
Subjects:
texture recognition
convolutional neural networks
non-additive entropy
image descriptors
Online Access:https://www.mdpi.com/1099-4300/23/10/1259

Internet

https://www.mdpi.com/1099-4300/23/10/1259

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