EfficientNet-based diabetic retinopathy image classification

Liying Feng

doi:10.1117/12.3026510

27 March 2024 EfficientNet-based diabetic retinopathy image classification

Liying Feng

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131050D (2024) https://doi.org/10.1117/12.3026510
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

Diabetic retinopathy is a common complication of diabetes that can lead to vision loss. Accurate detection of diabetic retinopathy is crucial for early intervention and treatment. This paper proposes a diabetic retinopathy detection method based on EfficientNet and optimizes the pooling layer. Experimental results conducted on the dataset provided by APTOS demonstrate that our approach achieves higher accuracy compared to other traditional methods. This study provides strong support for the early diagnosis and treatment of diabetic retinopathy and holds promising clinical applications.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liying Feng "EfficientNet-based diabetic retinopathy image classification", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131050D (27 March 2024); https://doi.org/10.1117/12.3026510

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