Didrpg2emtl_comp.rar Site

The architecture uses recurrence to reuse parameters across different stages of the de-raining process, which reduces the model size while improving its ability to handle complex rain patterns.

Code to run the de-rainer on the provided sample "Rain200L" or "Rain200H" datasets. DIDRPG2EMTL_comp.rar

The network focuses on learning the "rain residual" (the difference between the rainy image and the clean background), making the training process more stable and effective. Content of the .rar File The architecture uses recurrence to reuse parameters across

Settings for hyperparameters and directory paths used during the "comp" (computation/comparison) phase of the research. Performance and Impact DIDRPG2EMTL_comp.rar