mlsanityData to 13 Oct 2026

Asynchronous Bioplausible Neuron for SNN for Event Vision

arXiv 2311.11853 ↗First posted 20 Nov 2023cs.NE cs.CV q-bio.NCcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 15 of its 48 references that are in the map. First posted on arXiv 20 Nov 2023.

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15 of 48 references.

References · 15

  1. 2015Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccadescited by 313
  2. 2018Long short-term memory and learning-to-learn in networks of spiking neuronscited by 180
  3. 2021N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Camerascited by 92
  4. 2021Time-Ordered Recent Event (TORE) Volumes for Event Camerascited by 73
  5. 2021Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentationcited by 55
  6. 2018A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rulecited by 36
  7. 2022Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?cited by 25
  8. 2013Event-Driven Contrastive Divergence for Spiking Neuromorphic Systemscited by 14
  9. 2023A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perceptioncited by 13
  10. 2023Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Networkcited by 9
  11. 2016Deep Spiking Networkscited by 7
  12. 2023A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environmentcited by 7
3 more
  1. 2017Spiking neurons with short-term synaptic plasticity form superior generative networkscited by 6
  2. 2023A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networkscited by 6
  3. 2023Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Graspingcited by 5

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