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This paper presents the development of an industrial fall detection system utilizing YOLOv8 variants, enhanced by our proposed augmentation pipeline to increase dataset variance and improve detection accuracy. Among the models evaluated,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Gracile Astlin Pereira

This work introduces a fall detection system using the YOLOv5mu model, which achieved a mean average precision (mAP) of 0.995, demonstrating exceptional accuracy in identifying fall events within smart home environments. Enhanced by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Gracile Astlin Pereira

The utilization of deep learning-based object detection is an effective approach to assist visually impaired individuals in avoiding obstacles. In this paper, we implemented seven different YOLO object detection models \textit{viz}.,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Chenhao He , Pramit Saha

Detecting falls among the elderly and alerting their community responders can save countless lives. We design and develop a low-cost mobile robot that periodically searches the house for the person being monitored and sends an email to a…

Robotics · Computer Science 2024-08-13 Shihab Uddin Ahamad , Masoud Ataei , Vijay Devabhaktuni , Vikas Dhiman

This paper presents a generalized model for real-time detection of flying objects that can be used for transfer learning and further research, as well as a refined model that achieves state-of-the-art results for flying object detection. We…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Dillon Reis , Jordan Kupec , Jacqueline Hong , Ahmad Daoudi

This study explores a comprehensive approach to obstacle detection using advanced YOLO models, specifically YOLOv8, YOLOv7, YOLOv6, and YOLOv5. Leveraging deep learning techniques, the research focuses on the performance comparison of these…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Santiago Pérez , Camila Gómez , Matías Rodríguez

Video based fall detection accuracy has been largely improved due to the recent progress on deep convolutional neural networks. However, there still exists some challenges, such as lighting variation, complex background, which degrade the…

Computer Vision and Pattern Recognition · Computer Science 2021-08-02 Ziwei Chen , Yiye Wang , Wankou Yang

This research paper presents the development of an AI model utilizing YOLOv8 for real-time weapon detection, aimed at enhancing safety in public spaces such as schools, airports, and public transportation systems. As incidents of violence…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Ayush Thakur , Akshat Shrivastav , Rohan Sharma , Triyank Kumar , Kabir Puri

Computer vision, particularly vehicle and pedestrian identification is critical to the evolution of autonomous driving, artificial intelligence, and video surveillance. Current traffic monitoring systems confront major difficulty in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Md Nahid Sadik , Tahmim Hossain , Faisal Sayeed

One of the possible dangers that older people face in their daily lives is falling. Occlusion is one of the biggest challenges of vision-based fall detection systems and degrades their detection performance considerably. To tackle this…

Computer Vision and Pattern Recognition · Computer Science 2022-08-16 Sara Khalili , Hoda Mohammadzade , Mohammad Mahdi Ahmadi

Accurate fall detection for the assistance of older people is crucial to reduce incidents of deaths or injuries due to falls. Meanwhile, a vision-based fall detection system has shown some significant results to detect falls. Still,…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Sagar Chhetri , Abeer Alsadoon , Thair Al Dala in , P. W. C. Prasad , Tarik A. Rashid , Angelika Maag

The key to ensuring the safe obstacle avoidance function of autonomous driving systems lies in the use of extremely accurate vehicle recognition techniques. However, the variability of the actual road environment and the diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Haocheng Guo , Yaqiong Zhang , Lieyang Chen , Arfat Ahmad Khan

Fall detection in specialized homes for the elderly is challenging. Vision-based fall detection solutions have a significant advantage over sensor-based ones as they do not instrument the resident who can suffer from mental diseases. This…

Computer Vision and Pattern Recognition · Computer Science 2020-06-12 Alexy Carlier , Paul Peyramaure , Ketty Favre , Muriel Pressigout

Electric scooters (e-scooters) have rapidly emerged as a popular mode of transportation in urban areas, yet they pose significant safety challenges. In the United States, the rise of e-scooters has been marked by a concerning increase in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Dong Chen , Arman Hosseini , Arik Smith , Amir Farzin Nikkhah , Arsalan Heydarian , Omid Shoghli , Bradford Campbell

In recent years a growing interest on action recognition is observed, including detection of fall accident for the elderly. However, despite many efforts undertaken, the existing technology is not widely used by elderly, mainly because of…

Computer Vision and Pattern Recognition · Computer Science 2017-06-27 Michal Kepski

Timely and reliable detection of falls is a large and rapidly growing field of research due to the medical and financial demand of caring for a constantly growing elderly population. Within the past 2 decades, the availability of…

Human-Computer Interaction · Computer Science 2023-01-11 Harry Wixley

Falling is a commonly occurring mishap with elderly people, which may cause serious injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects of fall among the elderly people. Many fall monitoring…

Recently, a plethora of machine learning (ML) and deep learning (DL) algorithms have been proposed to achieve the efficiency, safety, and reliability of autonomous vehicles (AVs). The AVs use a perception system to detect, localize, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jalal Khan

The aging population is growing rapidly, and so is the danger of falls in older adults. A major cause of injury is falling, and detection in time can greatly save medical expenses and recovery time. However, to provide timely intervention…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Seyed Alireza Rahimi Azghadi , Truong-Thanh-Hung Nguyen , Helene Fournier , Monica Wachowicz , Rene Richard , Francis Palma , Hung Cao

Falls are serious and costly for elderly people. The Centers for Disease Control and Prevention of the US reports that millions of older people, 65 and older, fall each year at least once. Serious injuries such as; hip fractures, broken…

Computer Vision and Pattern Recognition · Computer Science 2017-08-16 Markus D. Solbach , John K. Tsotsos
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