Lithography hotspot detection through multi-scale feature fusion utilizing feature pyramid network and dense block-Reference-Cited by-同舟云学术

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Lithography hotspot detection through multi-scale feature fusion utilizing feature pyramid network and dense block

Published:2024-02-10 Issue:01 Volume:23 Page:
ISSN:2708-8340
Container-title:Journal of Micro/Nanopatterning, Materials, and Metrology
language:
Short-container-title:J. Micro/Nanopattern. Mats. Metro.

Author:

Xu Hui¹,Yuan Ye¹,Ma Ruijun¹,Qi Pan²,Tang Fuxin²,Xiao Xinzhong¹,Huang Wenxin¹,Liang Huaguo³

Affiliation:

1. Anhui University of Science and Technology, School of Computer Science and Engineering, Huainan, China

2. Anhui University of Science and Technology, School of Artificial Intelligence, Huainan, China

3. Hefei University of Technology, School of Microelectronics, Hefei, China

Publisher

SPIE-Intl Soc Optical Eng

Reference26 articles.

1. Semiconductor Manufacturing Technology at IBM

2. Aerial image metrology for OPC modeling and mask qualification

3. The lithography hotspot detection algorithm is based on improved Yolov5s;Wu,2023

4. Hotspot detection on post-OPC layout using full-chip simulation-based verification tool: a case study with aerial image simulation

5. Lithography simulation-based full-chip design analyses

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