AttGAN: attention gated generative adversarial network for spatio-temporal super-resolution of ocean phenomena

AttGAN: attention gated generative adversarial network for spatio-temporal super-resolution of ocean phenomena

This study proposes an innovative deep learning-aided approach based on generative adversarial networks named AttGAN, which is specialized for solving the spatio-temporal super-resolution problem of ocean datasets with complex waveforms and turbulent features. The proposed method can efficiently res...

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Detaylı Bibliyografya
Asıl Yazarlar: Yanni Liu, Xinjie Wang, Chunxin Yuan, Jiexin Xu, Zhiqiang Wei, Jie Nie
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: Taylor & Francis Group 2024-12-01
Seri Bilgileri:International Journal of Digital Earth
Konular:
Spatio-temporal super-resolution
AttGAN
attention gate
Online Erişim:https://www.tandfonline.com/doi/10.1080/17538947.2024.2368705

Internet

https://www.tandfonline.com/doi/10.1080/17538947.2024.2368705

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