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Updated: Jun 11, 2025

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多分辨率级联注意力U-Net用于光盘的定位和细分以及 fundus图像中的 fovea

R Shalini1, Varun P Gopi2

  • 1Department of Electronics and Communication Engineering, National Institute of Technology, 620015, Tiruchirappalli, Tamilnadu, India. rshalini080@gmail.com.

Scientific reports
|October 4, 2024
PubMed
概括

一个新的多分辨率级联注意力U-Net (MCAU-Net) 模型准确地识别了视网膜特征,如光盘 (OD) 和 fundus 图像中的 fovea. 这种深度学习方法通过提高细分和定位精度来改善视网膜疾病的自动查.

关键词:
废弃研究是废弃研究.注意模块的注意力模块.深度学习是一种深度学习.福维亚 (Fovea) 是一个常见的植物.热图回归回归是一种热图回归.多重分辨率的解决方案视觉光盘是指光盘中的光盘.波段变换的波段变换是什么

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