An imbalance aware lithography hotspot detection method based on HDAM and pre-trained GoogLeNet

Author:

Zhou KaiboORCID,Zhang KaifengORCID,Liu JieORCID,Liu Yanan,Liu ShiyuanORCID,Cao Guannan,Zhu JinlongORCID

Funder

PetroChina Innovation Foundation

Ministry of Industry

National Key Research

Publisher

IOP Publishing

Subject

Applied Mathematics,Instrumentation,Engineering (miscellaneous)

Reference32 articles.

1. On improving hotspot detection through synthetic pattern-based database enhancement;Reddy;IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.,2021

2. Semi-supervised hotspot detection with self-paced multitask learning;Chen;IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.,2019

3. Imbalance aware lithography hotspot detection: a deep learning approach;Yang;J. Micro/Nanolithogr. MEMS MOEMS,2017

4. Faster region-based hotspot detection;Chen;IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.,2020

5. Resolution enhancement techniques in optical lithography: it’s not just a mask problem;Liebmann,2001

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1. Methodology for Lithography Hotspot Detection using ResNet50V2 and Model soups;2024 International Conference on Electronics, Information, and Communication (ICEIC);2024-01-28

2. Lithography Hotspot Detection Based on Improved YOLOv3;ACTA OPT SIN;2023

3. Lithography Hotspot Detection Based on Improved Yolov5s;LASER OPTOELECTRON P;2023

4. Lithographic Hotspot Detection Using Adaptive Squish Pattern Sampling Combined with Faster R-CNN;2023 IEEE 15th International Conference on ASIC (ASICON);2023-10-24

5. A New Safe-Level Enabled Borderline-SMOTE for Condition Recognition of Imbalanced Dataset;IEEE Transactions on Instrumentation and Measurement;2023

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