Disjoint 15 5

Disjoint 15-5 is a specialized technical method designed for the field of computer vision, aiming to improve the accuracy and robustness of visual recognition tasks by optimizing feature representation and reducing overlap between categories. This method constructs two mutually independent subspaces to capture the unique attributes of different categories, thereby achieving more effective classification and recognition. Disjoint 15-5 has shown significant advantages in multi-class image classification, object detection, and scene understanding, effectively enhancing the model's generalization ability and recognition accuracy.