1(a), which comprises three key components: the BSCNN encoder, a model-driven decoder, and ILT training

Fast ILT based on the model-driven BSCNN The schematic diagram of the proposed method is illustrated i n Fig

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physics.optics · 2024-12-19 · conditional · novelty 4.0

A physics-driven U-net++ that outputs masks as stacks of rectangular blocks shows lower mask-writing shot counts with modest pattern-error increase.

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Fast inverse lithography based on a model-driven block stacking convolutional neural network physics.optics · 2024-12-19 · conditional · none · ref 3
A physics-driven U-net++ that outputs masks as stacks of rectangular blocks shows lower mask-writing shot counts with modest pattern-error increase.