Conversion of Siamese networks to spiking neural networks for energy-efficient object tracking-Reference-Cited by-同舟云学术

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Conversion of Siamese networks to spiking neural networks for energy-efficient object tracking

Published:2022-02-14 Issue:12 Volume:34 Page:9967-9982
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Luo Yihao,Shen Haibo,Cao Xiang,Wang Tianjiang,Feng Qi,Tan Zehan

Funder

national natural science foundation of china

huazhong university of science and technology

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-06984-1.pdf

Reference65 articles.

1. Basu A, Acharya J, Karnik T, Liu H, Li H, Seo JS, Song C (2018) Low-power, adaptive neuromorphic systems: recent progress and future directions. IEEE J Emerg Sel Top Circuits Syst 8(1):6–27

2. Bertinetto L, Valmadre J, Henriques JF, Vedaldi A, Torr PH (2016) Fully-convolutional siamese networks for object tracking. In: Proceedings of the European conference on computer vision (ECCV). Springer, pp 850–865

3. Bi GQ, Poo MM (1998) Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J Neurosci 18(24):10464–10472

4. Cao Y, Chen Y, Khosla D (2015) Spiking deep convolutional neural networks for energy-efficient object recognition. Int J Comput Vision 113(1):54–66

5. Cao Z, Cheng L, Zhou C, Gu N, Wang X, Tan M (2015) Spiking neural network-based target tracking control for autonomous mobile robots. Neural Comput Appl 26(8):1839–1847

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