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entropy regularization for flood depth super-resolution


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Created: Oct 14, 2024 at 5:27 p.m.
Last updated: Oct 14, 2024 at 6:09 p.m.
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Abstract

entropy regularization for flood depth super-resolution

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Content

README.md

the entropy weight can be modified in training.py

To run the CNN model for x2 upsampling

sh $ python main.py --dataset x2 --model cnn --model_id cnn_x2 To run the GAN models sh $ python main.py --dataset x2 --model gan --model_id cnn_x2

-- the datasets can be x2 x4 x8 or x16* other arguents are --epochs, --lr (learning rate), --number_residual_blocks, --weight_decay

How to Cite

el baida, m. (2024). entropy regularization for flood depth super-resolution, HydroShare, http://www.hydroshare.org/resource/50e33e9f6f7c4a95a404ae66fe356759

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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