The classification of diabetic retinopathy involves small differences between lesion points, resulting in minute variations among different categories of retinas. Consequently, the model struggles to distinguish between similar lesion images accurately. To enhance the model's classification accuracy, it must possess a more refined classification ability. The success of fine-grained classification models hinges on the model's ability to learn the relevant target features effectively.

不改变原意使其更有逻辑改写:In the diabetic retinopathy classification task the differences between tiny lesion points are small leading to very tiny differences between different categories of retinas and it is di

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