Hybrid SNN-based Privacy-Preserving Fall Detection using Neuromorphic Sensors-Reference-Cited by-同舟云学术

Hybrid SNN-based Privacy-Preserving Fall Detection using Neuromorphic Sensors

Published:2023-12-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing
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Author:

Prasad Shyam Sunder¹^ORCID,Mehta Naval Kishore¹^ORCID,Kumar Himanshu¹^ORCID,Banerjee Abeer¹^ORCID,Saurav Sumeet¹^ORCID,Singh Sanjay²^ORCID

Affiliation:

1. CSIR-Central Electronics Engineering Research Institute (CSIR-CEERI), IN and Academy of Scientific and Innovative Research (AcSIR), India

2. CSIR-Central Electronics Engineering Research Institute (CSIR-CEERI), India and Academy of Scientific and Innovative Research (AcSIR), India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627631.3627650

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4. Ahmed Nabil Belbachir, Stephan Schraml, and Aneta Nowakowska. 2011. Event-driven stereo vision for fall detection. In CVPR 2011 WORKSHOPS. IEEE, 78–83.

5. Tobias Bolten, Regina Pohle-Frohlich, and Klaus D Tonnies. 2021. DVS-OUTLAB: A Neuromorphic Event-Based Long Time Monitoring Dataset for Real-World Outdoor Scenarios. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 1348–1357.