Classification Consistency

Classification Consistency is an important task in the field of computer vision, aiming to evaluate the consistency of classification results for the same image under different transformations. This task analyzes the classification stability of images after transformations such as translation and rotation, ensuring the robustness and reliability of models in practical applications and enhancing their adaptability to input variations.