International Journal on Science and Technology

E-ISSN: 2229-7677   •   Impact Factor: 9.88

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Volume 17 Issue 2
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Automated Grading of Diabetic Retinopathy Using a Multi- Scale Deep Convolutional Neural Network with Attention Mechanism

Author(s) Ms. KM Sonam
Country India
Abstract Diabetic Retinopathy (DR) is a major cause of preventable blindness worldwide. This study proposes a Multi-Scale Deep Convolutional Neural Network with Channel-Spatial Attention Mechanism (MS-CNN-CSAM) for automated DR grading. Evaluated on EyePACS and APTOS datasets, the model achieved superior accuracy, demonstrating robust, efficient, and clinically applicable screening performance.
Keywords Diabetic Retinopathy, Convolutional Neural Network, Attention Mechanism, Multi-Scale Feature Extraction, Fundus Image Analysis, Deep Learning, Medical Image Classification, Class Imbalance, Quadratic Weighted Kappa
Field Computer Applications
Published In Volume 17, Issue 2, April-June 2026
Published On 2026-06-25
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