Keeping Deep Lithography Simulators Updated: Global–Local Shape-Based Novelty Detection and Active Learning-Reference-Cited by-同舟云学术

Keeping Deep Lithography Simulators Updated: Global–Local Shape-Based Novelty Detection and Active Learning

Published:2023-03 Issue:3 Volume:42 Page:1000-1014
ISSN:0278-0070
Container-title:IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
language:
Short-container-title:IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

Author:

Shao Hao-Chiang¹^ORCID,Ping Hsing-Lei²,Chen Kuo-Shiuan²,Su Weng-Tai²^ORCID,Lin Chia-Wen²^ORCID,Fang Shao-Yun³^ORCID,Tsai Pin-Yian⁴,Liu Yan-Hsiu⁵

Affiliation:

1. Institute of Data Science and Information Computing, National Chung Hsing University, Taichung, Taiwan

2. Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan

3. Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

4. Product Engineering Department, United Microelectronics Corporation, Hsinchu, Taiwan

5. Development of Smart Manufacturing, United Microelectronics Corporation, Hsinchu, Taiwan

Funder

Ministry of Science and Technology, Taiwan

United Microelectronics Corporation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software

Link

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3. Data-Driven Approaches for Process Simulation and Optical Proximity Correction;Proceedings of the 28th Asia and South Pacific Design Automation Conference;2023-01-16