Converting Artificial Neural Networks to Ultralow-Latency Spiking Neural Networks for Action Recognition-Reference-Cited by-同舟云学术

Converting Artificial Neural Networks to Ultralow-Latency Spiking Neural Networks for Action Recognition

Published:2024-08 Issue:4 Volume:16 Page:1533-1545
ISSN:2379-8920
Container-title:IEEE Transactions on Cognitive and Developmental Systems
language:
Short-container-title:IEEE Trans. Cogn. Dev. Syst.

Author:

You Hong¹^ORCID,Zhong Xian¹^ORCID,Liu Wenxuan¹^ORCID,Wei Qi²^ORCID,Huang Wenxin³^ORCID,Yu Zhaofei⁴^ORCID,Huang Tiejun⁵^ORCID

Affiliation:

1. Hubei Key Lab of Transportation Internet of Things, School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

2. School of Computer Science and Engineering, Nanyang Technological University, Singapore

3. School of Computer Science and Information Engineering, Hubei University, Wuhan, China

4. Institute for Artificial Intelligence, Peking University, Beijing, China

5. School of Computer Science and the Institute for Artifical Intelligence, Peking University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7274989/10633860/10466357.pdf?arnumber=10466357

Reference52 articles.

1. Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization

2. Dual-Recommendation Disentanglement Network for View Fuzz in Action Recognition

3. Fine-Grained Classification with Noisy Labels

4. Language models are few-shot learners;Brown,2020

5. Spiking Neuron Models

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