https://github.com/krisharul26/improvement-of-seat-belt-detection-via-instance-segmentation-using-yolact-
Wearing a seat belts can reduce the risk of serious injuries by 50%, reduce accidents by up to 45%, and save an average of 15,000 lives each year. This compulsion can be emphasized by monitoring and punishing the wear of seat belts by drivers. In that sense, the detection of seatbelt in the roads is crucial. Although several studies were focused on seat belt detection, some limitations and restrictions have not yet been resolved. Therefore, this study aims to detect the seat belt using instant segmentation approach with YOLACT ++ algorithm. Also, this study intends to detect the seat belt from the real-time video.
https://github.com/krisharul26/improvement-of-seat-belt-detection-via-instance-segmentation-using-yolact-
Last synced: 3 months ago
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Wearing a seat belts can reduce the risk of serious injuries by 50%, reduce accidents by up to 45%, and save an average of 15,000 lives each year. This compulsion can be emphasized by monitoring and punishing the wear of seat belts by drivers. In that sense, the detection of seatbelt in the roads is crucial. Although several studies were focused on seat belt detection, some limitations and restrictions have not yet been resolved. Therefore, this study aims to detect the seat belt using instant segmentation approach with YOLACT ++ algorithm. Also, this study intends to detect the seat belt from the real-time video.
- Host: GitHub
- URL: https://github.com/krisharul26/improvement-of-seat-belt-detection-via-instance-segmentation-using-yolact-
- Owner: KrishArul26
- Created: 2021-12-05T08:30:41.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2021-12-05T08:30:41.000Z (almost 4 years ago)
- Last Synced: 2025-02-23T08:30:47.083Z (8 months ago)
- Size: 1000 Bytes
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Improvement-Of-Seat-Belt-Detection-Via-Instance-Segmentation-Using-YOLACT-
Wearing a seat belts can reduce the risk of serious injuries by 50%, reduce accidents by up to 45%, and save an average of 15,000 lives each year. This compulsion can be emphasized by monitoring and punishing the wear of seat belts by drivers. In that sense, the detection of seatbelt in the roads is crucial. Although several studies were focused on seat belt detection, some limitations and restrictions have not yet been resolved. Therefore, this study aims to detect the seat belt using instant segmentation approach with YOLACT ++ algorithm. Also, this study intends to detect the seat belt from the real-time video.