Scale Generalisation

Scale Generalisation refers to the ability of computer vision models to maintain stable performance across different scales. Its goal is to optimize algorithms and data augmentation techniques so that the model can effectively identify and process multi-scale image features, thereby enhancing the robustness and generalization capability of the model. In practical applications, Scale Generalisation is of great value for improving the accuracy of tasks such as object detection and image segmentation.