Structure Aware Generative Adversarial Networks for Hyperspectral Image Classification

Structure Aware Generative Adversarial Networks for Hyperspectral Image Classification

Generative adversarial networks (GANs) have shown striking performances in computer vision applications to augment virtual training samples (VTS). However, the VTS generating by GANs in the context of hyperspectral image classification suffer from structural inconsistency due to the insufficient num...

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Bibliographic Details
Main Authors: Tayeb Alipour-Fard, Hossein Arefi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning (DL)
hyperspectral images (HSIs)
convolutional neural network (CNN)
generative adversarial networks (GANs)
remote sensing
Online Access:https://ieeexplore.ieee.org/document/9187967/

Internet

https://ieeexplore.ieee.org/document/9187967/

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