Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning
Joint Authors
Luo, Shengyuan
Li, Xiumin
Yi, Hao
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Electrophysiological studies have shown that mammalian primary visual cortex are selective for the orientations of visual stimuli.
Inspired by this mechanism, we propose a hierarchical spiking neural network (SNN) for image classification.
Grayscale input images are fed through a feed-forward network consisting of orientation-selective neurons, which then projected to a layer of downstream classifier neurons through the spiking-based supervised tempotron learning rule.
Based on the orientation-selective mechanism of the visual cortex and tempotron learning rule, the network can effectively classify images of the extensively studied MNIST database of handwritten digits, which achieves 96% classification accuracy based on only 2000 training samples (traditional training set is 60000).
Compared with other classification methods, our model not only guarantees the biological plausibility and the accuracy of image classification but also significantly reduces the needed training samples.
Considering the fact that the most commonly used deep learning neural networks need big data samples and high power consumption in image recognition, this brain-inspired computational neural network model based on the layer-by-layer hierarchical image processing mechanism of the visual cortex may provide a basis for the wide application of spiking neural networks in the field of intelligent computing.
American Psychological Association (APA)
Li, Xiumin& Yi, Hao& Luo, Shengyuan. 2020. Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning. Neural Plasticity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1202936
Modern Language Association (MLA)
Li, Xiumin…[et al.]. Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning. Neural Plasticity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1202936
American Medical Association (AMA)
Li, Xiumin& Yi, Hao& Luo, Shengyuan. Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning. Neural Plasticity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1202936
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202936