Super-resolution of sea surface temperature with convolutional neural network- and generative adversarial network-based methods

Super-resolution of sea surface temperature with convolutional neural network- and generative adversarial network-based methods

In this paper, we perform the super-resolution of sea surface temperature data with the enhanced super-resolution generative adversarial network (ESRGAN), which is a deep neural network-based single-image super-resolution (SISR) method that uses a generative adversarial network (GAN). We generate hi...

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Bibliographic Details
Main Authors: Tomoki Izumi, Motoki Amagasaki, Kei Ishida, Masato Kiyama
Format: Article
Language:English
Published: IWA Publishing 2022-04-01
Series:Journal of Water and Climate Change
Subjects:
convolutional neural network
esrgan
generative adversarial network
rrdbnet
single-image super-resolution
Online Access:http://jwcc.iwaponline.com/content/13/4/1673

Internet

http://jwcc.iwaponline.com/content/13/4/1673

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