TrackNet for badminton tracking using tensorflow2
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Updated
Jun 30, 2024 - Python
TrackNet for badminton tracking using tensorflow2
Implementation of paper - TrackNetV3: Enhancing ShuttleCock Tracking with Augmentations and Trajectory Rectification
TrackNetV3 : Beyond TrackNetV2 ,and "First" TrackNet using Attention
PicoBETH (Badminton Electronic Tension Machine Head) built with Raspberry Pi Pico for badminton stringing — now supporting tennis as well.
Official Implementation for ShuttleNet: Position-aware Fusion of Rally Progress and Player Styles for Stroke Forecasting in Badminton (AAAI'22)
Badminton coach ai: A badminton match data analysis platform based on deep learning (Physical Education Journal'20)
Code for our paper, "BADGE: BADminton report Generation and Evaluation with LLM," presented at the IJCAI 2024 Workshop IT4PSS.
ZeroBETH is an open-source badminton and tennis stringing machine built on the Raspberry Pi Zero, with a focus on being economical, intuitive, and accurate. ZeroBETH 是一款基於 Raspberry Pi Zero 的開源羽毛球與網球穿線機,致力於實現經濟性、直覺操作與高精度的設計理念。
Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton Matches (ICDM'21)
Shuttlecock hitting event detection and rally analysis in badminton using computer vision (TrackNet/YOLO) and machine learning (F0/F1 feature sets) for match winner prediction.
Two-stage badminton bounce detection: CatBoost candidate generator + CNN+BiLSTM refiner.
Badminton match analytics desktop app — stroke annotation, Markov chain EPV, Bayesian real-time analysis & coach reports
A badminton match scheduler for amateur and semi-competitive players.
Cross-platform mobile training app for badminton players and runners with AI-powered personalized training plans
Reservation bot built with Python and Selenium that reserves badminton fields at high efficiency.
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