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Spiking neural network (SNN), as a brain-inspired energy-efficient neural network, has attracted the interest of researchers.
Networks of spiking neurons: the third generation of neural network models
Wolfgang Maass · 1997
Earlier work this paper cites.
Truenorth: Design and tool flow of a 65 mw 1 million neuron programmable neurosynaptic chip
Filipp Akopyan, Jun Sawada, Andrew Cassidy, Rodrigo Alvarez-Icaza, John Arthur, Paul Merolla, Nabil Imam, Yutaka Nakamura, Pallab Datta, Gi-Joon Nam, et al · 2015
Earlier work this paper cites.
Spiking deep convolutional neural networks for energy-efficient object recognition
Yongqiang Cao, Yang Chen, and Deepak Khosla · 2015
Earlier work this paper cites.
Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing
Peter U Diehl, Daniel Neil, Jonathan Binas, Matthew Cook, Shih-Chii Liu, and Michael Pfeiffer · 2015
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Conversion of continuous-valued deep networks to efficient event-driven networks for image classification
Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu, Michael Pfeiffer, and Shih-Chii Liu · 2017
Earlier work this paper cites.
Improving multi-layer spiking neural networks by incorporating brain-inspired rules
Yi Zeng, Tielin Zhang, and Bo Xu · 2017
Earlier work this paper cites.
Loihi: A neuromorphic manycore processor with on-chip learning
Mike Davies, Narayan Srinivasa, Tsung-Han Lin, Gautham Chinya, Yongqiang Cao, Sri Harsha Choday, Georgios Dimou, Prasad Joshi, Nabil Imam, Shweta Jain, et al · 2018
Earlier work this paper cites.
Deep neural networks with weighted spikes
Jaehyun Kim, Heesu Kim, Subin Huh, Jinho Lee, and Kiyoung Choi · 2018
Earlier work this paper cites.
Mutual inhibition of lateral inhibition: a network motif for an elementary computation in the brain
Minoru Koyama and Avinash Pujala · 2018
Cited alongside, same era.
Spatio-temporal backpropagation for training high-performance spiking neural networks
Yujie Wu, Lei Deng, Guoqi Li, Jun Zhu, and Luping Shi · 2018
Cited alongside, same era.
Towards spike-based machine intelligence with neuromorphic computing
Kaushik Roy, Akhilesh Jaiswal, and Priyadarshini Panda · 2019
Cited alongside, same era.
Going deeper in spiking neural networks: Vgg and residual architectures
Abhronil Sengupta, Yuting Ye, Robert Wang, Chiao Liu, and Kaushik Roy · 2019
Cited alongside, same era.
Tdsnn: From deep neural networks to deep spike neural networks with temporal-coding
Lei Zhang, Shengyuan Zhou, Tian Zhi, Zidong Du, and Yunji Chen · 2019
Cited alongside, same era.
Siamsnn: Siamese spiking neural networks for energy-efficient object tracking
Yihao Luo, Min Xu, Caihong Yuan, Xiang Cao, Liangqi Zhang, Yan Xu, Tianjiang Wang, and Qi Feng · 2020
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Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, and Kaushik Roy · 2020
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Strategy and benchmark for converting deep q-networks to event-driven spiking neural networks
Weihao Tan, Devdhar Patel, and Robert Kozma · 2020
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Optimal conversion of conventional artificial neural networks to spiking neural networks
Shikuang Deng and Shi Gu · 2021
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Deep spiking neural network: Energy efficiency through time based coding
Bing Han and Kaushik Roy · 2020
Cited alongside, same era.
Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network
Bing Han, Gopalakrishnan Srinivasan, and Kaushik Roy · 2020
Cited alongside, same era.
Spiking-yolo: Spiking neural network for energy-efficient object detection
Seijoon Kim, Seongsik Park, Byunggook Na, and Sungroh Yoon · 2020
Cited alongside, same era.
Jianhao Ding, Zhaofei Yu, Yonghong Tian, and Tiejun Huang · 2021
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Yang Li, Yi Zeng, and Dongcheng Zhao · 2021
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A free lunch from ann: Towards efficient, accurate spiking neural networks calibration
Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, and Shi Gu · 2021
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Diet-snn: A low-latency spiking neural network with direct input encoding and leakage and threshold optimization
Nitin Rathi and Kaushik Roy · 2021
Later among the works it cites.