Combining Spiking Neural Network and Artificial Neural Network for Enhanced Image Classification

• URL: http://arxiv.org/abs/2102.10592v1
• Date: Sun, 21 Feb 2021 12:03:16 GMT
• Title: Combining Spiking Neural Network and Artificial Neural Network for Enhanced Image Classification
• Authors: Naoya Muramatsu and Hai-Tao Yu
• Abstract summary: spiking neural networks (SNNs) that more closely resemble biological brain synapses have attracted attention owing to their low power consumption. We build versatile hybrid neural networks (HNNs) that improve the concerned performance.
• Score: 1.8411688477000185
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: With the continued innovations of deep neural networks, spiking neural networks (SNNs) that more closely resemble biological brain synapses have attracted attention owing to their low power consumption. However, for continuous data values, they must employ a coding process to convert the values to spike trains. Thus, they have not yet exceeded the performance of artificial neural networks (ANNs), which handle such values directly. To this end, we combine an ANN and an SNN to build versatile hybrid neural networks (HNNs) that improve the concerned performance.

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