CCGAN as a Tool for Satellite-Derived Chlorophyll <i>a</i> Concentration Gap Reconstruction

CCGAN as a Tool for Satellite-Derived Chlorophyll <i>a</i> Concentration Gap Reconstruction

This work represents a modification of the Context Conditional Generative Adversarial Network as a novel implementation of a non-linear gap reconstruction approach of missing satellite-derived chlorophyll <i>a</i> concentration data. By adjusting the loss functions of the network to focu...

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Bibliographic Details
Main Authors: Leon Ćatipović, Frano Matić, Hrvoje Kalinić, Shubha Sathyendranath, Tomislav Županović, James Dingle, Thomas Jackson
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Journal of Marine Science and Engineering
Subjects:
GAN
generative adversarial network
reconstruction
satellite chlorophyll <i>a</i>
Online Access:https://www.mdpi.com/2077-1312/11/9/1814

Internet

https://www.mdpi.com/2077-1312/11/9/1814

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