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Author

Yu-Lung Chang

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Open access Sep 2026

Triple-Path Kolmogorov–Arnold Networks with Deep Mutual Learning for Robust Retinal Microvascular Segmentation

This work proposes a novel, highly efficient Triple-Path Kolmogorov–Arnold Network (KAN) optimized via Deep Mutual Learning (DML), which establishes a robust, accurate, and clinically viable solution for automated point-of-care retinal diagnostics.

Yu-Lung Chang, Yen-Ching Chang · 0 citations
Conference Aug 2026

Optimizing multi-dimensional retinal segmentation: a performance-practicality analysis

This research evaluates the performance of SegNet, U-Net, and DeepLab across in-domain, cross-domain, and mixed-domain scenarios, demonstrating that lightweight models often offer the optimal balance between performance and operational efficiency.

Yu-Lung Chang, Wei-Chun Chi, Yen-Ching Chang · 1 citation · ⚡1

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