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This research establish a new novel Dynamic SwishNet – 181, a neural network for timely Diabetic Retinopathy (DR) detection. Diabetic Retinopathy (DR) image preprocessing is using the integration between CLAHE - Contrast Limited Adaptive Histogram Equalization and ADF - Anisotropic Diffusion Filtering. Results of evaluation against VGG16, EfficientNet, and RESNET with a promising tool for efficient DR screening. Deep learning with image enhancement approach is used to avoid in eye vision loss for diabetic patients.

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Using Dynamic SwishNet – 181 to Enhancing Diabetic Retinopathy Detection and Severity Classification

  • 会议论文

  • 发表日期：

    2026年

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  • K. Kayathri,
  • K. Kavitha

摘要

This research establish a new novel Dynamic SwishNet – 181, a neural network for timely Diabetic Retinopathy (DR) detection. Diabetic Retinopathy (DR) image preprocessing is using the integration between CLAHE - Contrast Limited Adaptive Histogram Equalization and ADF - Anisotropic Diffusion Filtering. Results of evaluation against VGG16, EfficientNet, and RESNET with a promising tool for efficient DR screening. Deep learning with image enhancement approach is used to avoid in eye vision loss for diabetic patients.