ResBaGAN: A Residual Balancing GAN with Data Augmentation for Forest Mapping

Although deep learning techniques are known to achieve outstanding classification accuracies, remote sensing datasets often present limited labeled data and class imbalances, two challenges to attaining high levels of accuracy. In recent years, the GAN architecture has achieved great success as a da...

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Bibliographic Details
Main Authors: Alvaro G. Dieste, Francisco Arguello, Dora B. Heras
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10141632/