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Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review
Xin-Ru Feng, Heng-Chao Li, Rui Wang +3
Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI). Nonnegative matrix fa…
Adaptive Cross-Attention-Driven Spatial-Spectral Graph Convolutional Network for Hyperspectral Image Classification
Jin-Yu Yang, Heng-Chao Li, Wen-Shuai Hu +2
Recently, graph convolutional networks (GCNs) have been developed to explore spatial relationship between pixels, achieving better classification performance of hyperspectral image…
A3CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification
Heng-Chao Li, Wen-Shuai Hu, Wei Li +3
The problem of effectively exploiting the information multiple data sources has become a relevant but challenging research topic in remote sensing. In this paper, we propose a new…
SSCU-Net: Spatial-Spectral Collaborative Unmixing Network for Hyperspectral Images
Lin Qi, Feng Gao, Junyu Dong +2
Linear spectral unmixing is an essential technique in hyperspectral image processing and interpretation. In recent years, deep learning-based approaches have shown great promise in…
Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image Classification
Junjie Wang, Feng Gao, Junyu Dong +1
In recent years, hyperspectral image (HSI) classification based on generative adversarial networks (GAN) has achieved great progress. GAN-based classification methods can mitigate…