As the chip size continues to decrease, the feature size of transistor is getting closer to the optical diffraction limit. When performing the lithography process, the optical proximity effect exists due to the mismatch between the exposure wavelength and the critical dimension of the mask pattern, making it difficult to obtain results on the wafer that are consistent with target pattern. To alleviate this effect, we propose an Optical Proximity Correction (OPC) method with an improved Encoder-Decoder structure. By embedding a coordinate information convolution module, the limitations of the convolution module in dealing with spatial location information are broken through. Moreover, a residual connection is introduced between encoder and decoder, which allows the algorithm to further improve the model's ability to deal with complex layout data by learning the residuals between the inputs and the outputs. The results show that compared with other deep learning algorithms, the proposed method obtains ideal correction results while speeding up the computation.
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