Label data volume and distribution of basketball instances: (a) Number of basketball instances; (b) Central coordinates and size distribution of labeled boxes; (c) Length and width distribution of labeled boxes.

Label data volume and distribution of basketball instances: (a) Number of basketball instances; (b) Central coordinates and size distribution of labeled boxes; (c) Length and width distribution of labeled boxes.

<p>Label data volume and distribution of basketball instances: (a) Number of basketball instances; (b) Central coordinates and size distribution of labeled boxes; (c) Length and width distribution of labeled boxes.</p>

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Bibliographic Details
Main Author:	Zeyu Liang (4813593) (author)
Other Authors:	Jiuyuan Wang (9447020) (author), Tianhao Huang (13874389) (author), Zilong Sang (22127027) (author), Jia Zhang (187802) (author)
Published:	2025
Subjects:	Neuroscience Sociology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> accurate reducing false positives optimizing tactical planning optimizing feature attention global attention mechanism experimental results show effective feature extraction changing camera angles calculating similarity features advancements significantly enhance partially occluded scenes model &# 8217 15 %, ensuring yolov8 </ p mean average precision map ), achieving basketball detection based enhances detection accuracy basketball detection occluded scenarios model integrates ensuring fairness timely detection reliable detection basketball targets time performance study introduces statistically significant spectator experience scene complexity interference environments f1 score dynamically adjusts data analysis c2f increases 2 %. 001 ).
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