Acta Optica Sinica, Volume. 43, Issue 3, 0312008(2023)
Lithography Hotspot Detection Method Based on Pre-trained VGG11 Model
[1] Wang X Z, Dai F Z, Li S K et al[M]. Integrated circuit and lithographic tool(2020).
[2] Neisser M. International roadmap for devices and systems lithography roadmap[J]. Journal of Micro/Nanopatterning, Materials, and Metrology, 20, 044601(2021).
[4] Jochemsen M, Anunciado R, Timoshkov V et al. Process window limiting hot spot monitoring for high-volume manufacturing[J]. Proceedings of SPIE, 9778, 97781R(2016).
[5] Hunsche S, Jochemsen M, Jain V et al. A new paradigm for in-line detection and control of patterning defects[J]. Proceedings of SPIE, 9424, 94241B(2015).
[6] Weisbuch F, Thaler T, Buttgereit U et al. Improving ORC methods and hotspot detection with the usage of aerial images metrology[J]. Proceedings of SPIE, 11327, 113270D(2020).
[7] Kim J, Fan M H. Hotspot detection on post-OPC layout using full-chip simulation-based verification tool: a case study with aerial image simulation[J]. Proceedings of SPIE, 5256, 919-925(2003).
[8] Nosato H, Sakanashi H, Takahashi E et al. Hotspot prevention and detection method using an image-recognition technique based on higher-order local autocorrelation[J]. Journal of Micro/Nanolithography, MEMS, and MOEMS, 13, 011007(2014).
[9] Gupta P, Kahng A B, Nakagawa S et al. Lithography simulation-based full-chip design analyses[J]. Proceedings of SPIE, 6156, 61560T(2006).
[10] Yang F, Sinha S, Chiang C et al. Improved tangent space based distance metric for lithographic hotspot classification[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 36, 1545-1556(2017).
[11] Yao H, Sinha S, Chiang C et al. Efficient process-hotspot detection using range pattern matching[C], 625-632(2006).
[12] Ding D, Wu X, Ghosh J et al. Machine learning based lithographic hotspot detection with critical-feature extraction and classification[C], 219-222(2009).
[13] Nagase N, Suzuki K, Takahashi K et al. Study of hot spot detection using neural networks judgment[J]. Proceedings of SPIE, 6607, 66071B(2007).
[14] Nakamura S, Matsunawa T, Kodama C et al. Clean pattern matching for full chip verification[J]. Proceedings of SPIE, 8327, 83270T(2012).
[15] Yu Y T, Lin G H, Jiang I H R et al. Machine-learning-based hotspot detection using topological classification and critical feature extraction[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 34, 460-470(2013).
[16] Ding D, Torres J A, Pan D Z. High performance lithography hotspot detection with successively refined pattern identifications and machine learning[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 30, 1621-1634(2011).
[17] Shin M, Lee J H. Accurate lithography hotspot detection using deep convolutional neural networks[J]. Journal of Micro/Nanolithography, MEMS, and MOEMS, 15, 043507(2016).
[18] Zhang H, Yang H Y, Yu B et al. VLSI layout hotspot detection based on discriminative feature extraction[C], 542-545(2016).
[19] Yu B, Gao J R, Ding D et al. Accurate lithography hotspot detection based on principal component analysis-support vector machine classifier with hierarchical data clustering[J]. Journal of Micro/Nanolithography, MEMS, and MOEMS, 14, 011003(2014).
[20] Shin M, Lee J H. CNN based lithography hotspot detection[J]. The International Journal of Fuzzy Logic and Intelligent Systems, 16, 208-215(2016).
[21] Yang H Y, Lin Y J, Yu B et al. Lithography hotspot detection: from shallow to deep learning[C], 233-238(2017).
[22] Matsunawa T, Nojima S, Kotani T. Automatic layout feature extraction for lithography hotspot detection based on deep neural network[J]. Proceedings of SPIE, 9781, 97810H(2016).
[23] Xiao Y D, Huang X Q. Learning lithography hotspot detection from ImageNet[C], 266-273(2019).
[24] Zhou K B, Zhang K F, Liu J et al. An imbalance aware lithography hotspot detection method based on HDAM and pre-trained GoogLeNet[J]. Measurement Science and Technology, 32, 125008(2021).
[25] Russakovsky O, Deng J, Su H et al. ImageNet large scale visual recognition challenge[J]. International Journal of Computer Vision, 115, 211-252(2015).
[26] Liao L F, Li S K, Che Y Q et al. Lithography hotspot detection method based on transfer learning using pre-trained deep convolutional neural network[J]. Applied Sciences, 12, 2192(2022).
[27] Zhou Z H. Model selection and evaluation[M]. Machine learning, 25-55(2021).
[28] Torres J A. ICCAD-2012 CAD contest in fuzzy pattern matching for physical verification and benchmark suite[C], 349-350(2012).
[29] Yang H Y, Luo L Y, Su J et al. Imbalance aware lithography hotspot detection: a deep learning approach[J]. Journal of Micro/Nanolithography, MEMS, and MOEMS, 16, 033504(2017).
[30] Zhou Z H. Linear models[M]. Machine learning, 57-77(2021).
Get Citation
Copy Citation Text
Lufeng Liao, Sikun Li, Xiangzhao Wang. Lithography Hotspot Detection Method Based on Pre-trained VGG11 Model[J]. Acta Optica Sinica, 2023, 43(3): 0312008
Category: Instrumentation, Measurement and Metrology
Received: Jul. 6, 2022
Accepted: Aug. 31, 2022
Published Online: Feb. 13, 2023
The Author Email: Li Sikun (lisikun@siom.ac.cn), Wang Xiangzhao (wxz26267@siom.ac.cn)