Litho-AsymVnet: super-resolution lithography modeling with an asymmetric V-net architecture
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11432-022-3755-y.pdf
Reference4 articles.
1. Mack C A. Thirty years of lithography simulation. In: Proceedings of SPIE, 2005. 5754: 1–12
2. Ye W, Alawieh M B, Lin Y B, et al. LithoGAN: end-to-end lithography modeling with generative adversarial networks. In: Proceedings of ACM/IEEE Design Automation Conference (DAC), 2019. 1–6
3. Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation. In: Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015. 234–241
4. Zhang Q, Zhang Y, Li J, et al. Litho-NeuralODE 2.0: improving hotspot detection accuracy with advanced data augmentation, DCT-based features, and neural ordinary differential equations. Integration, 2022, 85: 10–19
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Budget Analysis of Multiple Parameters in EUV Lithography System Based on Support Vector Machine;2024 2nd International Symposium of Electronics Design Automation (ISEDA);2024-05-10
2. Dynamic budget analysis of multiple parameters in a lithography system based on the superposition of light intensity fluctuations;Optics Express;2024-01-30
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