YOLO-Net: A lightweight edge-enhanced detection model for small-object recognition in tennis match scenarios
Xiangyu Du, Tao Wang, Weiwei Zu, Xianjing Dong, Liangquan Jia · 2026
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Description
Du and colleagues built a compact vision system for spotting small objects in tennis matches in a 2026 study. The ball moves fast, players block views, and backgrounds are busy, so standard detectors often miss key items. Their system sharpens edges, weighs image channels more wisely, and punishes errors on hard small targets more strongly.
The team also labeled a new set of more than six thousand match images showing players, rackets, and balls. The system beat its base version on accuracy while staying small and fast enough for live use. Such a tool could support referees, coaches reviewing tactics, and broadcasters adding live graphics.
Catalog record
| CREATOR | Xiangyu Du, Tao Wang, Weiwei Zu, Xianjing Dong, Liangquan Jia |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42487 |
| LICENSE | CC_BY |
| RIGHTS | CC BY |
| SOURCE | PLOS |