Research on basketball goal recognition and sports analysis based on improved Yolo V7 detection algorithm

In the constantly advancing wave of artificial intelligence, accurate goal determination and motion recognition analysis have become one of the key technologies to improve the level of sports competition. To this end, a dual camera goal recognition method based on improved Yolo V7 is proposed. This method introduces a Hierarchical Attention Information Guidance (HAIG) module and replaces it with the XIOU loss function to improve the accuracy and real-time performance of the Yolo V7 algorithm in basketball goal detection. The dual camera setup combined with multi view fusion strategy ensures the accuracy and robustness of goal discrimination. The results show that the improved Yolo V7 algorithm performs well in basketball goal recognition tasks. In the basketball dataset constructed for research, the detection accuracy can reach 98.5%, and the detection speed of a single image can reach 0.003s/sheet, achieving accurate and efficient judgment. This not only promotes the development of basketball analysis technology, but also provides reference for other object detection tasks.