Hotspot detection using squish-net-Reference-Cited by-同舟云学术

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Hotspot detection using squish-net

Published:2019-03-20 Issue: Volume: Page:
ISSN:
Container-title:Design-Process-Technology Co-optimization for Manufacturability XIII
language:
Short-container-title:

Author:

Yang Haoyu,Pathak Piyush,Gennari Frank E.,Lai Ya-Chieh,Yu Bei

Publisher

SPIE

Reference22 articles.

1. ICCAD-2012 CAD contest in fuzzy pattern matching for physical verification and benchmark suite;Torres,2012

2. “ITRS.” http://www.itrs.net.

3. Imbalance aware lithography hotspot detection: a deep learning approach;Yang;Journal of Micro/Nanolithography, MEMS, and MOEMS (JM3),2017

4. Accurate lithography hotspot detection using deep convolutional neural networks

5. Optical proximity correction with hierarchical bayes model;Matsunawa,2015

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1. Geometrical positioning surveying-based features for BEOL line-end-pull-back modeling using regression-based machine-learning;Journal of Micro/Nanopatterning, Materials, and Metrology;2023-06-29

2. Can We Trust Machine Learning for Electronic Design Automation?;2021 IEEE 34th International System-on-Chip Conference (SOCC);2021-09-14

3. Adversarial Perturbation Attacks on ML-based CAD;ACM Transactions on Design Automation of Electronic Systems;2020-10-02

4. Foundry approach for layout risk assessment through comprehensive pattern harvesting and large-scale data analysis;Design-Process-Technology Co-optimization for Manufacturability XIV;2020-03-23

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