Nowadays most of the researches aimed for studying artificial neural networks and in particular convolutional neural networks for the impressive results in several scientific fields. However, these methodologies need of post-hoc technique for improving their interpretability and explainability. In the last years, fuzzy systems are raising great interest for the simplicity to develop trustworthy and explainable systems. This work aims to introduce a fuzzy relational neural network based model for extrapolating relevant information from images data permitting to obtain a clearer indication on the classification processes. Encouraging results are obtained on benchmark data sets.

Advanced Fuzzy Relational Neural Network

Di Nardo E.;Ciaramella A.
2021

Abstract

Nowadays most of the researches aimed for studying artificial neural networks and in particular convolutional neural networks for the impressive results in several scientific fields. However, these methodologies need of post-hoc technique for improving their interpretability and explainability. In the last years, fuzzy systems are raising great interest for the simplicity to develop trustworthy and explainable systems. This work aims to introduce a fuzzy relational neural network based model for extrapolating relevant information from images data permitting to obtain a clearer indication on the classification processes. Encouraging results are obtained on benchmark data sets.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/101617
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