Asynchronous Bioplausible Neuron for SNN for Event Vision
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866909948448866304 |
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| author | Kachole, Sanket Sajwani, Hussain Naeini, Fariborz Baghaei Makris, Dimitrios Zweiri, Yahya |
| author_facet | Kachole, Sanket Sajwani, Hussain Naeini, Fariborz Baghaei Makris, Dimitrios Zweiri, Yahya |
| contents | Spiking Neural Networks (SNNs) offer a biologically inspired approach to computer vision that can lead to more efficient processing of visual data with reduced energy consumption. However, maintaining homeostasis within these networks is challenging, as it requires continuous adjustment of neural responses to preserve equilibrium and optimal processing efficiency amidst diverse and often unpredictable input signals. In response to these challenges, we propose the Asynchronous Bioplausible Neuron (ABN), a dynamic spike firing mechanism to auto-adjust the variations in the input signal. Comprehensive evaluation across various datasets demonstrates ABN's enhanced performance in image classification and segmentation, maintenance of neural equilibrium, and energy efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_11853 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Asynchronous Bioplausible Neuron for SNN for Event Vision Kachole, Sanket Sajwani, Hussain Naeini, Fariborz Baghaei Makris, Dimitrios Zweiri, Yahya Neural and Evolutionary Computing Computer Vision and Pattern Recognition Neurons and Cognition Spiking Neural Networks (SNNs) offer a biologically inspired approach to computer vision that can lead to more efficient processing of visual data with reduced energy consumption. However, maintaining homeostasis within these networks is challenging, as it requires continuous adjustment of neural responses to preserve equilibrium and optimal processing efficiency amidst diverse and often unpredictable input signals. In response to these challenges, we propose the Asynchronous Bioplausible Neuron (ABN), a dynamic spike firing mechanism to auto-adjust the variations in the input signal. Comprehensive evaluation across various datasets demonstrates ABN's enhanced performance in image classification and segmentation, maintenance of neural equilibrium, and energy efficiency. |
| title | Asynchronous Bioplausible Neuron for SNN for Event Vision |
| topic | Neural and Evolutionary Computing Computer Vision and Pattern Recognition Neurons and Cognition |
| url | https://arxiv.org/abs/2311.11853 |