Optimized Framework for High-Speed Object Detection in Badminton Using Deep Learning (eBook, PDF)
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Research Paper (undergraduate) from the year 2024 in the subject Engineering - Computer Engineering, grade: Graduate, , course: Graduate B.E, language: English, abstract: Object detection is an important task in sports analysis, particularly in badminton, where the high-speed motion of the shuttlecock can make it challenging to detect. Here, we suggest a badminton high-speed object detection system using YOLO, a real-time object detection model. Our system is trained on a dataset of badminton images and videos, along with corresponding object annotations. The performance of our system is evalu...
Research Paper (undergraduate) from the year 2024 in the subject Engineering - Computer Engineering, grade: Graduate, , course: Graduate B.E, language: English, abstract: Object detection is an important task in sports analysis, particularly in badminton, where the high-speed motion of the shuttlecock can make it challenging to detect. Here, we suggest a badminton high-speed object detection system using YOLO, a real-time object detection model. Our system is trained on a dataset of badminton images and videos, along with corresponding object annotations. The performance of our system is evaluated using several metrics, including mean average precision, precision, recall, F1-score, and speed. The results show that our system can achieve high accuracy and real-time performance, making it suitable for use in badminton analysis applications. Our system can be used to detect and track the shuttlecock in real-time, providing valuable insights into the game, such as the speed and trajectory of the shuttlecock, which can be used to improve the performance of players and coaches.
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