Overlapped 15 5

Overlapped 15-5 is an advanced technical framework targeting computer vision, aimed at improving the accuracy and efficiency of image recognition and processing by optimizing feature overlap and sparse representation. This method effectively enhances the robustness and generalization capability of the model by achieving an overlap rate of 15% to 5% on multi-scale feature maps, making it suitable for tasks such as object detection and image segmentation in complex scenarios, with significant application value.