Convolutional Spiking Neural Network for Image Classification

• URL: http://arxiv.org/abs/2505.08514v1
• Date: Tue, 13 May 2025 12:47:13 GMT
• Title: Convolutional Spiking Neural Network for Image Classification
• Authors: Mikhail Kiselev, Andrey Lavrentyev,
• Abstract summary: We consider an implementation of convolutional architecture in a spiking neural network (SNN) used to classify images.<n>As in the traditional neural network, the convolutional layers form informational "features" used as predictors in the SNN-based classifier with CoLaNET architecture.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We consider an implementation of convolutional architecture in a spiking neural network (SNN) used to classify images. As in the traditional neural network, the convolutional layers form informational "features" used as predictors in the SNN-based classifier with CoLaNET architecture. Since weight sharing contradicts the synaptic plasticity locality principle, the convolutional weights are fixed in our approach. We describe a methodology for their determination from a representative set of images from the same domain as the classified ones. We illustrate and test our approach on a classification task from the NEOVISION2 benchmark.

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