English(EN) SePArate: Segmenting Patterns from Defects in Wafer Manufacturing Using Weak Supervision

新的弱监督方法改进了晶圆缺陷分割

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

研究人员开发了SePArate，一种用于分割半导体晶圆制造中缺陷的新型弱监督方法。该方法仅使用图像级标注来实现模式的像素级分离，相比于难以进行根本原因分析的现有自动化检测方法有了显著改进。SePArate采用三阶段训练过程，包括编码器预训练和知识迁移，以准确分割缺陷，并在实验评估中证明了其优于基线方法的性能。 AI

影响该方法可以增强半导体制造中的自动化检测，从而实现更有效的根本原因分析和流程优化。

排序理由该集群包含一篇详细介绍针对特定技术问题的[lever_c_demoted from research: ic=1 ai=1.0]新方法的学术论文。

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Dain Kwon, Changmin Shin, Sunjong Park, Kanghyun Choi, Hyeyoon Lee, Jaewon Jang, Minseok Choi, Jinho Lee · 2026-09-01 04:00

SePArate：利用弱监督从晶圆制造缺陷中分割模式

arXiv:2608.30410v1 Announce Type: cross Abstract: In semiconductor manufacturing, defect analysis is essential, but manual inspection cannot scale. However, existing automated inspection methods remain insufficient for root-cause analysis and process optimization. To this end, we…

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SePArate：利用弱监督从晶圆制造缺陷中分割模式

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