Human Fall Detection using YOLO: A Real-Time and AI-on-the-Edge Perspective
Author:
Affiliation:
1. University of Engineering and Technology Taxila Pakistan.,Department of Computer Engineering
2. School of Electronic Engineering and Computer Science, Queen Mary University of London,London,U.K.,El 4NS
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9854043/9853852/09854070.pdf?arnumber=9854070
Reference24 articles.
1. Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm
2. A novel fall detection algorithm for elderly using SHIMMER wearable sensors
3. IoT based fall detection and ambient assisted system for the elderly
4. Development of an Enhanced Threshold-Based Fall Detection System Using Smartphones With Built-In Accelerometers
5. Fall-Detection Algorithm Using Plantar Pressure and Acceleration Data
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4. Fall detection paradigm for embedded devices based on YOLOv8;2023 IEEE International Conference on Imaging Systems and Techniques (IST);2023-10-17
5. CAGn: High-Order Coordinated Attention Module for Improving Fall Detection Models;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16
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