Morphological Convolutional Neural Network Architecture for Digit Recognition

Deep neural networks have proved promising results in many applications and fields, but they are still assimilated to a black box. Thus, it is very useful to introduce interpretability aspects to prevent the blind application of deep networks. This paper proposed an interpretable morphological convo...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2019-09, Vol.30 (9), p.2876-2885
Hauptverfasser:	Mellouli, Dorra, Hamdani, Tarek M., Sanchez-Medina, Javier J., Ben Ayed, Mounir, Alimi, Adel M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Benchmarks Computer architecture Convolution Convolutional neural network (CNN) deep neural networks (DNNs) Feature maps Image recognition interpretability morphological CNN (Morph-CNN) Morphological operations morphological operators Morphology Neural networks Neurons Pattern recognition Task analysis
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