Remote Sensing Data Augmentation Through Adversarial Training

Remote Sensing Data Augmentation Through Adversarial Training

The lack of remote sensing images and poor quality limit the performance improvement of follow-up research such as remote sensing interpretation. In this article, a generative adversarial network (GAN) is proposed for data augmentation of remote sensing images abstracted from Jiangxi and Anhui Provi...

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Bibliographic Details
Main Authors: Ning Lv, Hongxiang Ma, Chen Chen, Qingqi Pei, Yang Zhou, Fenglin Xiao, Ji Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Data augmentation
deep supervision
downsampling
GAN
Online Access:https://ieeexplore.ieee.org/document/9531488/

Internet

https://ieeexplore.ieee.org/document/9531488/

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