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  • A Computer Vision-Based System to Help Health Professionals . . .
    In addition, it lays the future foundations for creating a Cloud-based platform for remote fall risk assessment and its integration with a mobile assistant robot, and for designing Artificial Intelligence models that can detect patterns and identify pathologies for enabling therapists to prevent falls in users under risk
  • Deep feature fusion with computer vision driven fall . . .
    By leveraging cameras and complicated approaches, a computer vision (CV) system can monitor residents’ movements continuously and identify any potential fall events in real time
  • Technical insights into vision-based fall detection systems . . .
    Vision-based fall detection systems have made significant strides in advancing safety and health monitoring, particularly for elderly and high-risk populations This review has emphasized the critical role of data preprocessing and feature extraction in improving system accuracy and robustness
  • Detecting Falls With Computer Vision | Chooch
    The benefits of detecting falls using action detection, computer vision and edge AI outweigh the costs By reducing the risk of falls and the costs that come with delayed fall response, AI models provide our partners and customers with real value
  • ElderFallGuard: Real-Time IoT and Computer Vision-Based Fall . . .
    In order to overcome this difficulty, we present ElderFallGuard: A Computer Vision Based IoT Solution for Elderly Fall Detection and Notification, a cutting-edge, non-invasive system intended for quick caregiver alerts and real-time fall detection
  • A Novel Computer Vision-Based Approach to Mitigating Fall . . .
    In this paper, an intelligent deep learning and computer vision based elderly fall recognition system is designed which utilizes advanced spatial-channel decoupled downsampling in You Only Look Once version 10 (YOLOv10), pytorch, darknet and cascaded CNN technologies for the fall detection





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