Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction-Reference-Cited by-同舟云学术

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Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction

Published:2023-05-04 Issue:6 Volume:55 Page:6979-6995
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Samadzadeh Ali,Far Fatemeh Sadat Tabatabaei,Javadi Ali,Nickabadi Ahmad,Chehreghani Morteza Haghir

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-023-11247-8.pdf

Reference51 articles.

1. Sharmin S et al (2019) A comprehensive analysis on adversarial robustness of spiking neural networks. IEEE, pp 1–8

2. Kim H, Leutenegger S, Davison AJ (2016) Real-time 3d reconstruction and 6-dof tracking with an event camera. Springer, pp 349–364

3. Kueng B, Mueggler E, Gallego G, Scaramuzza D (2016) Low-latency visual odometry using event-based feature tracks. IEEE, pp 16–23

4. Rebecq H, Horstschäfer T, Gallego G, Scaramuzza D (2016) Evo: a geometric approach to event-based 6-dof parallel tracking and mapping in real time. IEEE Robot Autom Lett 2(2):593–600

5. Gallego G et al (2017) Event-based, 6-dof camera tracking from photometric depth maps. IEEE Trans Pattern Anal Mach Intell 40(10):2402–2412

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