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Here are the codes for the "3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer" paper.

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3DUNetGSFormer

Here is the codes developed for our paper titled "3DUNetGSFormer: A Deep Learning Pipeline for Complex Wetland Mapping using Generative Adversarial Networks and Swin Transformer" published in Ecological Informatics journal.

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Cite our paper at:

Ali Jamali, Masoud Mahdianpari, Brian Brisco, Dehua Mao, Bahram Salehi, Fariba Mohammadimanesh, 3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer, Ecological Informatics, 2022, 101904, ISSN 1574-9541, https://doi.org/10.1016/j.ecoinf.2022.101904. (https://www.sciencedirect.com/science/article/pii/S1574954122003545)

Ali Jamali, Masoud Mahdianpari, Brian Brisco, Dehua Mao, Bahram Salehi, Fariba Mohammadimanesh, 3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer, Ecological Informatics, Volume 72, 2022, 101904, ISSN 1574-9541, https://doi.org/10.1016/j.ecoinf.2022.101904.

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Here are the codes for the "3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer" paper.

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