Disjoint 19 1

Disjoint 19-1 is a multi-label classification method designed for computer vision tasks, aiming to address the issue of mutual exclusivity among labels by optimizing the label assignment strategy. This enhances the model's recognition accuracy and robustness in complex scenarios, and it is widely applied in image annotation, object detection, and other fields.