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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…
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…
Superpixel-guided Discriminative Low-rank Representation of Hyperspectral Images for Classification
Shujun Yang, Junhui Hou, Yuheng Jia +2
In this paper, we propose a novel classification scheme for the remotely sensed hyperspectral image (HSI), namely SP-DLRR, by comprehensively exploring its unique characteristics,…
More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification
Danfeng Hong, Lianru Gao, Naoto Yokoya +4
Classification and identification of the materials lying over or beneath the Earth's surface have long been a fundamental but challenging research topic in geoscience and remote se…