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Deep Learning-Driven Inverse Lithography Technology for Dmd-Based Maskless Projection Lithography

https://doi.org/10.2139/ssrn.4658626
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inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-extracted
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1016/j.optlastec.2018.02.005openalex-extracted
Emerging applications of digital micromirror devices in biophotonic fields
inferredcites →https://doi.org/10.1016/j.optlastec.2019.01.001openalex-extracted
Maskless lithography based on digital micromirror device (DMD) and double sided microlens and spatial filter array
inferredcites →https://doi.org/10.1021/acs.nanolett.1c00559openalex-extracted
λ/12 Super Resolution Achieved in Maskless Optical Projection Nanolithography for Efficient Cross-Scale Patterning
inferredcites →https://doi.org/10.1063/1.4967373openalex-extracted
Lithographic resolution enhancement of a maskless lithography system based on a wobulation technique for flow lithography
inferredcites →https://doi.org/10.1063/1.5030585openalex-extracted
Multi-scale structure patterning by digital-mask projective lithography with an alterable projective scaling system
inferredcites →https://doi.org/10.1109/access.2018.2877587openalex-extracted
Classification for Dermoscopy Images Using Convolutional Neural Networks Based on Region Average Pooling
inferredcites →https://doi.org/10.1109/dac.2018.8465816openalex-extracted
GAN-OPC: Mask Optimization with Lithography-guided Generative Adversarial Nets
inferredcites →https://doi.org/10.1109/dac18072.2020.9218530openalex-extracted
Deep Learning-Driven Simultaneous Layout Decomposition and Mask Optimization
inferredcites →https://doi.org/10.1109/dac18072.2020.9218706openalex-extracted
Adaptive Layout Decomposition with Graph Embedding Neural Networks
inferredcites →https://doi.org/10.1109/iccad51958.2021.9643464openalex-extracted
DevelSet: Deep Neural Level Set for Instant Mask Optimization
inferredcites →https://doi.org/10.1109/tcad.2019.2939329openalex-extracted
GAN-OPC: Mask Optimization With Lithography-Guided Generative Adversarial Nets
inferredcites →https://doi.org/10.1109/tcad.2021.3061494openalex-extracted
Deep Learning-Driven Simultaneous Layout Decomposition and Mask Optimization
inferredcites →https://doi.org/10.1109/tcad.2021.3109556openalex-extracted
Neural-ILT 2.0: Migrating ILT to Domain-Specific and Multitask-Enabled Neural Network
inferredcites →https://doi.org/10.1109/tcad.2022.3140729openalex-extracted
Adaptive Layout Decomposition With Graph Embedding Neural Networks
inferredcites →https://doi.org/10.1109/tcad.2022.3175939openalex-extracted
A GPU-Enabled Level-Set Method for Mask Optimization
inferredcites →https://doi.org/10.1109/tcad.2023.3286262openalex-extracted
DevelSet: Deep Neural Level Set for Instant Mask Optimization
inferredcites →https://doi.org/10.1109/tvlsi.2016.2616840openalex-extracted
A Fast Process-Variation-Aware Mask Optimization Algorithm With a Novel Intensity Modeling
inferredcites →https://doi.org/10.1117/1.jmm.20.3.030901openalex-extracted
Inverse lithography technology: 30 years from concept to practical, full-chip reality
inferredcites →https://doi.org/10.1117/12.2257871openalex-extracted
Accurate lithography simulation model based on convolutional neural networks
inferredcites →https://doi.org/10.1117/12.2279780openalex-extracted
Accurate lithography simulation model based on convolutional neural networks
inferredcites →https://doi.org/10.1117/12.2583662openalex-extracted
Deep learning-based hotspot prediction of via printability in process window corners
inferredcites →https://doi.org/10.1117/12.655904openalex-extracted
OPC and PSM design using inverse lithography: a nonlinear optimization approach
inferredcites →https://doi.org/10.1117/12.681857openalex-extracted
Inverse Lithography Technology (ILT): what is the impact to the photomask industry?
inferredcites →https://doi.org/10.1117/12.848252openalex-extracted
Toward a consistent and accurate approach to modeling projection optics
inferredcites →https://doi.org/10.1364/josaa.25.002960openalex-extracted
Binary mask optimization for inverse lithography with partially coherent illumination
inferredcites →https://doi.org/10.1364/oe.25.016854openalex-extracted
Batch fabrication of functional optical elements on a fiber facet using DMD based maskless lithography
inferredcites →https://doi.org/10.1364/oe.26.032565openalex-extracted
Model-driven convolution neural network for inverse lithography
inferredcites →https://doi.org/10.1364/oe.381503openalex-extracted
Intensity modulation based optical proximity optimization for the maskless lithography
inferredcites →https://doi.org/10.1364/oe.448231openalex-extracted
Maximizing energy utilization in DMD-based projection lithography
inferredcites →https://doi.org/10.1364/oe.472495openalex-extracted
Label-free neural networks-based inverse lithography technology
inferredcites →https://doi.org/10.1364/oe.493665openalex-extracted
Genetic algorithm-based optical proximity correction for DMD maskless lithography
inferredcites →https://doi.org/10.1364/ol.415788openalex-extracted
Lithographic pattern quality enhancement of DMD lithography with spatiotemporal modulated technology
inferredcites →https://doi.org/10.1364/ol.488122openalex-extracted
Generating an M 2 × N 2 spot array with a dual-period hybrid Dammann grating fabricated using maskless projection lithography
inferredcites →https://doi.org/10.1364/optica.406304openalex-extracted
Submicrometer-scale pattern generation via maskless digital photolithography
inferredcites →https://doi.org/10.1364/opticaopen.23949384openalex-extracted
inferredcites →https://doi.org/10.1515/nanoph-2022-0021openalex-extracted
Photonic crystal L3 cavity laser fabricated using maskless digital photolithography
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1912.01703openalex-extracted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-extracted
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
inferredcites →https://doi.org/10.1364/ao.503332openalex-snapshot
Inverse lithography physics-informed deep neural level set for mask optimization
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