CG-Net: A Novel End-to-end Framework for Fall Detection from Videos-Reference-Cited by-同舟云学术

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CG-Net: A Novel End-to-end Framework for Fall Detection from Videos

Published:2023-04-21 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Computer and Communication Systems (ICCCS)
language:
Short-container-title:

Author:

Cheng Yuning¹,Chen Gao²,Zhou Qingfeng²,Liu Chanzi²,Cai Chuanbao³

Affiliation:

1. School of Computer Science and Technology, Dongguan University of Technology,Dongguan,China

2. School of Electrical Engineering and Intelligentization, Dongguan University of Technology,Dongguan,China

3. Shen Zhen Everwin Precision Technology Co.,LTD,Shenzhen,China

Funder

NSFC, China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10150427/10150444/10151063.pdf?arnumber=10151063

Reference21 articles.

1. An improved tiny-yolov3 pedestrian detection algorithm

2. Yolov3: An incremental improvement;redmon;ArXiv Preprint,2018

3. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

4. RMPE: Regional Multi-person Pose Estimation

5. Falls Prediction Based on Body Keypoints and Seq2Seq Architecture

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