Image recognition based on sparse spike neural network

Yuanlei Yang; Yan Mo; Lidan Wang; Shukai Duan

doi:10.1117/12.2652781

20 October 2022 Image recognition based on sparse spike neural network

Yuanlei Yang, Yan Mo, Lidan Wang, Shukai Duan

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123501F (2022) https://doi.org/10.1117/12.2652781
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

Spiking neural networks (SNNs) has made great achievements in pattern recognition. Among the existing SNNs, unsupervised SNNs, especially those using spike-time-dependent plasticity (STDP), have a biological mechanism more in line with human brain cognition and are considered to have great potential in simulating the learning process of the biological brain. However, most of the existing SNNs based on STDP will be directly or indirectly used in the full connection layer, which leads to large computational overhead and over-training of the network. On the basis of predecessors, this paper uses the concurrent sparse spike neural network and achieves very good recognition accuracy when the number of synapses is reduced by nearly 1/10.

Citation Download Citation

Yuanlei Yang, Yan Mo, Lidan Wang, and Shukai Duan "Image recognition based on sparse spike neural network", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123501F (20 October 2022); https://doi.org/10.1117/12.2652781

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