Reducing Systematic Defects using Calibre Wafer Defect Engineering and Machine Learning Solutions-Reference-Cited by-同舟云学术

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Reducing Systematic Defects using Calibre Wafer Defect Engineering and Machine Learning Solutions

Published:2020-11-05 Issue: Volume: Page:
ISSN:
Container-title:2020 International Workshop on Advanced Patterning Solutions (IWAPS)
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Author:

Jiang Jet,Hou Frank,Li Gavin,Chen Summy,Fei Marfei,Xie Qian,Cao Liang,Wan Qijian,Hu Xinyi,Du Chunshan,Wang David,Huang Elven,Paninjath Sankaranarayanan,Madhusudhan Saikiran,Tian Leo

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9286788/9286789/09286791.pdf?arnumber=9286791

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effective Downsampling Techniques for SEM Defect Inspection Using Design Insights in Machine Learning: Topic/category: DI: Defect Inspection and Reduction;2024 35th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC);2024-05-13

2. Using machine learning method to improve design sampling efficiency for fab applications;DTCO and Computational Patterning III;2024-04-10

3. Using pattern analysis to improve process window qualification cycle time;DTCO and Computational Patterning III;2024-04-10

4. Wafer yield prediction using AI: potentials and pitfalls;Metrology, Inspection, and Process Control XXXVII;2023-04-27

5. Layout Hotspot Pattern Clustering Using a Density-based Approach;2023 International VLSI Symposium on Technology, Systems and Applications (VLSI-TSA/VLSI-DAT);2023-04-17

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