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A Review of the Application of Deep Learning in the Classification of Diabetic Retinopathy
Traditional image object classification algorithms and strategies are difficult to meet the requirements of image processing efficiency, performance, and intelligence. In recent years, deep learning in the computer vision has made great progress, showing good application prospects in medical image reading. Firstly, the background of deep learning and the knowledge of convolutional neural networks are introduced to fundamentally understand the basic model architecture and optimization methods of deep learning applied in the medical image. Secondly, the classification method of diabetic retinopathy images is discussed specifically. Finally, the problems faced in the future are analyzed.
A Review of the Application of Deep Learning in the Classification of Diabetic Retinopathy
Traditional image object classification algorithms and strategies are difficult to meet the requirements of image processing efficiency, performance, and intelligence. In recent years, deep learning in the computer vision has made great progress, showing good application prospects in medical image reading. Firstly, the background of deep learning and the knowledge of convolutional neural networks are introduced to fundamentally understand the basic model architecture and optimization methods of deep learning applied in the medical image. Secondly, the classification method of diabetic retinopathy images is discussed specifically. Finally, the problems faced in the future are analyzed.
A Review of the Application of Deep Learning in the Classification of Diabetic Retinopathy
Stud. in Distributed Intelligence
Yuan, Xiaohui (editor) / Elhoseny, Mohamed (editor) / Yu, Xuyan (author) / Liu, Jianxia (author) / Xue, Wenxuan (author)
2020-06-26
13 pages
Article/Chapter (Book)
Electronic Resource
English
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