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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection

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成果类型:
期刊论文
作者:
Zheng, Jiayi;Wan, Yaping;Yang, Xin;Zhong, Hua;Du, Minghua;...
通讯作者:
Wang, G
作者机构:
[Zheng, Jiayi; Wan, Yaping; Zhong, Hua] Univ South China, Dept Comp, Hengyang, Peoples R China.
[Yang, Xin; Zheng, Jiayi; Wang, Gang] Beijing Inst Basic Med Sci, Ctr Brain Sci, Beijing, Peoples R China.
[Du, Minghua] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Emergency, Beijing, Peoples R China.
[Wang, Gang] Chinese Inst Brain Res, Beijing, Peoples R China.
通讯机构:
[Wang, G ] B
Beijing Inst Basic Med Sci, Ctr Brain Sci, Beijing, Peoples R China.
Chinese Inst Brain Res, Beijing, Peoples R China.
语种:
英文
关键词:
bio-inspired vision computation;drone target recognition;motion detection;motion saliency estimation;spiking neural networks;visual motion features
期刊:
Frontiers in Computational Neuroscience
ISSN:
1662-5188
年:
2025
卷:
19
页码:
1452203
基金类别:
Beijing Nova Program [2022038]; National Natural Science Foundation of China [62102443]; Hunan Provincial Natural Science Foundation Key Joint Project Between Province [2024JJ7428]
机构署名:
本校为第一机构
院系归属:
计算机科学与技术学院
摘要:
Traditional object detection methods usually underperform when locating tiny or small drones against complex backgrounds, since the appearance features of the targets and the backgrounds are highly similar. To address this, inspired by the magnocellular motion processing mechanisms, we proposed to utilize the spatial-temporal characteristics of the flying drones based on spiking neural networks, thereby developing the Magno-Spiking Neural Network (MG-SNN) for drone detection. The MG-SNN can learn to identify potential regions of moving targets through motion saliency estimation and subsequentl...

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