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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Detalles Bibliográficos
Autores principales: Florindo, Joao, Metze, Konradin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534779/
https://www.ncbi.nlm.nih.gov/pubmed/34681983
http://dx.doi.org/10.3390/e23101259

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534779/
https://www.ncbi.nlm.nih.gov/pubmed/34681983
http://dx.doi.org/10.3390/e23101259

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