SpikeGoogle: Spiking Neural Networks with GoogLeNet-like inception module

CAAI Transactions on Intelligence Technology

article

Xuan Wang¹  Minghong Zhong¹  Hoiyuen Cheng¹  Junjie Xie¹  Yingchu Zhou²  Jun Ren³  Mengyuan Liu¹ 

[1] School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China, Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology;Shenzhen Academy of Metrology and Quality Inspection;Infocare Systems Limited

关键词: GoogLeNet;    inception;    Spiking Neural Networks;   

DOI  :  10.1049/cit2.12082

学科分类：数学（综合）

来源: Wiley

【 摘 要 】

Spiking Neural Network is known as the third-generation artificial neural network whose development has great potential. With the help of Spike Layer Error Reassignment in Time for error back-propagation, this work presents a new network called SpikeGoogle, which is implemented with GoogLeNet-like inception module. In this inception module, different convolution kernels and max-pooling layer are included to capture deep features across diverse scales. Experiment results on small NMNIST dataset verify the results of the authors’ proposed SpikeGoogle, which outperforms the previous Spiking Convolutional Neural Network method by a large margin.

【 授权许可】

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