曲线子分辨率通过数据驱动的U-Net模型协助功能放置

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Updated: Jan 10, 2026

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

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Jiale Liu1, Wenjing He1, Wenhao Ding1

  • 1School of Automation, Guangdong University of Technology, Mega Education Center South, Guangzhou 510006, China.

Micromachines
|November 27, 2025
PubMed
概括

本研究介绍了一种深度学习框架,用于优化半导体制造中的次分辨率辅助特性 (SRAF). 人工智能模型大大加速了SRAF的改进,提供了高模式保真性和降低计算成本.

关键词:
优化 SRAFs 的优化.这就是U-Net.计算 lithography 的使用方法.卷积神经网络 (CNN) 是一种神经网络.深度学习是一种深度学习.反向光刻技术的反向光刻技术.设定水平的方法方法.石版模型模型的模型.面具优化优化 面具优化光学近距离校正的校正方法

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