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- W2986339180 abstract "In this paper, we propose to apply a deep multi-scale encoder-decoder neural network (MsEN-Net) for SAR images enhancement method based on scale-recurrent network (SRN), which consists of encoder and decoder modules trained by the coarse to fine strategy. Simulation with fixed speed errors and experiments with real data are implemented and evaluated by peak signal to noise ratio and structural similarity. Experimental results with both visual and quantitative analysis demonstrate the competitive performance of our proposed method." @default.
- W2986339180 created "2019-11-22" @default.
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- W2986339180 date "2019-07-01" @default.
- W2986339180 modified "2023-09-28" @default.
- W2986339180 title "SAR Images Enhancement Via Deep Multi-Scale Encoder-Decoder Neural Network" @default.
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- W2986339180 doi "https://doi.org/10.1109/igarss.2019.8898690" @default.
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