Dual-Branch Spectral–Spatial Adversarial Representation Learning for Hyperspectral Image Classification With Few Labeled Samples

Recently, deep learning methods, particularly the convolutional neural networks, have been extensively employed for extracting spectral–spatial features in hyperspectral image (HSI) classification tasks, yielding promising results. Conventional methods often use small image patches as input a...

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Bibliografische Detailangaben

Hauptverfasser:	Caihao Sun, Xiaohua Zhang, Hongyun Meng, Xianghai Cao, Jinhua Zhang, Licheng Jiao
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2023-01-01
Schriftenreihe:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Schlagworte:	Adversarial network class consistency loss dual branch generative adversarial network (GAN) hyperspectral image (HSI) classification semisupervised
Online-Zugang:	https://ieeexplore.ieee.org/document/10168240/
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