Lithography pattern alignment using generative adversarial network

Yunhyoung Nam; Do-Nyun Kim

doi:10.1117/12.3010395

10 April 2024 Lithography pattern alignment using generative adversarial network

Yunhyoung Nam, Do-Nyun Kim

Proceedings Volume 12955, Metrology, Inspection, and Process Control XXXVIII; 129552R (2024) https://doi.org/10.1117/12.3010395
Event: SPIE Advanced Lithography + Patterning, 2024, San Jose, California, United States

Conference Poster

Abstract

The accurate alignment between the reference layout, also known as the target pattern, and the scanning electron microscope (SEM) image is an essential undertaking in the die-to-database (D2DB) inspection within the semiconductor industry. In this study, we provide a novel approach that facilitates accurate pattern alignment between them by applying a generative adversarial network (GAN).

Citation Download Citation

Yunhyoung Nam and Do-Nyun Kim "Lithography pattern alignment using generative adversarial network", Proc. SPIE 12955, Metrology, Inspection, and Process Control XXXVIII, 129552R (10 April 2024); https://doi.org/10.1117/12.3010395

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