Real-Time Human Fall Detection Using a Lightweight Pose Estimation Technique-Reference-Cited by-同舟云学术

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Real-Time Human Fall Detection Using a Lightweight Pose Estimation Technique

Published:2023-11-30 Issue: Volume: Page:30-40
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Alam Ekram,Sufian Abu,Dutta Paramartha,Leo Marco

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-48879-5_3

Reference22 articles.

1. Alam, E., Sufian, A., Dutta, P., Leo, M.: Vision-based human fall detection systems using deep learning: a review. Comput. Biol. Med. 146, 105626 (2022)

2. Wang, Z., Ramamoorthy, V., Gal, U., Guez, A.: Possible life saver: a review on human fall detection technology. Robotics 9(3), 55 (2020)

3. Gutiérrez, J., Rodríguez, V., Martin, S.: Comprehensive review of vision-based fall detection systems. Sensors 21(3), 947 (2021)

4. Alam, E., Sufian, A., Das, A.K., Bhattacharya, A., Ali, M.F., Rahman, M.H.: Leveraging deep learning for computer vision: a review. In: 2021 22nd International Arab Conference on Information Technology (ACIT), pp. 1–8. IEEE (2021)

5. Wang, X., Ellul, J., Azzopardi, G.: Elderly fall detection systems: a literature survey. Front. Robot. AI 7, 71 (2020)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Omobot: a low-cost mobile robot for autonomous search and fall detection;2024 IEEE International Conference on Advanced Intelligent Mechatronics (AIM);2024-07-15

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