The behavior of lesions in diabetic retina varies depending on the period, and there is a high similarity in lesion images between adjacent categories. However, the small differences in samples significantly limit the performance improvement of the model, making it challenging to achieve the desired robust state [5]. To address these issues, this paper proposes an improved network model that outperforms the state-of-the-art. The remainder of this paper is structured as follows: Section 2 provides a brief overview of related work on the diagnosis of diabetic retinopathy. Section 3 presents the backbone model based on a deep neural network. Section 4 discusses the experimental results, and Section 5 concludes our work

不改变原意使其更有逻辑改写:The lesions behave differently in different periods of diabetic retina and the similarity of lesion images between adjacent categories is large The small difference in samples severely l

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