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Deep learning network for detecting tennis court
Unofficial PyTorch implementation of TrackNet
This computer vision project analyzes tennis match videos using cutting-edge techniques. It employs YOLOv8 for player detection, finetuned YOLO for ball tracking, and ResNet50 for extracting court …
This project analyzes Tennis players in a video to measure their speed, ball shot speed and number of shots. This project will detect players and the tennis ball using YOLO and also utilizes CNNs t…
This model generalizes to unseen badminton videos and aims to outperform traditional techniques like YOLO + Kalman or TrackNetV2.
[BMVC2023] Widely Applicable Strong Baseline for Sports Ball Detection and Tracking
The University of Auckland Badminton Clubs Website
TrackNetV3 : Beyond TrackNetV2 ,and "First" TrackNet using Attention
Implementation of paper - TrackNetV3: Enhancing ShuttleCock Tracking with Augmentations and Trajectory Rectification
TrackNet for badminton tracking using tensorflow2
Official research projects of badminton CoachAI
This project utilizes computer vision techniques to detect players and shuttlecocks in badminton games.
In this group project carried out with @Anannyap7, the aim is to take a professional badminton match video as an input and predict the most probable space on the court where the shot will be hit by…
Image augmentation for machine learning experiments.
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