Research on diabetic retinopathy image classification model based on convolutional neural network
Aiming to address the issue of automatic classification of diabetic retinopathy,this paper introduces model for classifying diabetic retinopathy images based on convolutional neural network.The model utilizes two structures,MobileNet and DenseNet,as the backbone networks,and incorporates a category weight function and attention mechanism for enhancement.The experimental results on the Aptos-2019 dataset,which consists of five categories,demonstrate that the diabetic retinopathy classification model proposed in this paper can efficiently identify lesion images,achieving an accuracy of 0.8310 in the five-category task.
NETL
NSTL
万方数据
