Deep learning in DFM applications (Conference Presentation)

Tetsuaki Matsunawa; Shigeki Nojima

doi:10.1117/12.2503462

12 October 2018 Deep learning in DFM applications (Conference Presentation)

Tetsuaki Matsunawa, Shigeki Nojima

Author Affiliations +

Proceedings Volume 10810, Photomask Technology 2018; 1081006 (2018) https://doi.org/10.1117/12.2503462
Event: SPIE Photomask Technology + Extreme Ultraviolet Lithography, 2018, Monterey, California, United States

Abstract

Machine learning is a powerful tool to learn a predictive model which can give a statistical or probabilistic solution to a problem. It has widely been applied to major issues in design for manufacturing field, such as SRAF generation, compact resist model and lithography hotspot detection. Although it is sometimes considered as an effective technique that solves serious problems, a reliable solution is rarely achieved without detailed understanding of the problem and appropriate problem formulation. In this paper, we will discuss basic concept and recent results of machine learning applications in design for manufacturing.

Conference Presentation

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Tetsuaki Matsunawa and Shigeki Nojima "Deep learning in DFM applications (Conference Presentation)", Proc. SPIE 10810, Photomask Technology 2018, 1081006 (12 October 2018); https://doi.org/10.1117/12.2503462

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