Spectral–Spatial Attention Feature Extraction for Hyperspectral Image Classification Based on Generative Adversarial Network

Spectral–Spatial Attention Feature Extraction for Hyperspectral Image Classification Based on Generative Adversarial Network

Recent research shows that generative adversarial network (GAN) based deep learning derived frameworks can improve the accuracy of hyperspectral image (HSI) classification on limited labeled samples. However, several studies point out that existing GAN-based methods are heavily affected by the compl...

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Bibliographic Details
Main Authors: Hongbo Liang, Wenxing Bao, Xiangfei Shen, Xiaowu Zhang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Attention module
generative adversarial network (GAN)
hyperspectral image (HSI) classification
semisupervised deep learning
spectral–spatial information
Online Access:https://ieeexplore.ieee.org/document/9551774/

Internet

https://ieeexplore.ieee.org/document/9551774/

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