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SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
Danfeng Hong, Zhu Han, Jing Yao +4
Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepanci…
An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery
Xuan Yang, Shanshan Li, Zhengchao Chen +5
Semantic segmentation is an essential part of deep learning. In recent years, with the development of remote sensing big data, semantic segmentation has been increasingly used in r…
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
Danfeng Hong, Lianru Gao, Jing Yao +4
Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneous…
FCCDN: Feature Constraint Network for VHR Image Change Detection
Pan Chen, Danfeng Hong, Zhengchao Chen +3
Change detection is the process of identifying pixelwise differences in bitemporal co-registered images. It is of great significance to Earth observations. Recently, with the emerg…
Using Low-rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing
Lianru Gao, Zhicheng Wang, Lina Zhuang +3
Tensor-based methods have been widely studied to attack inverse problems in hyperspectral imaging since a hyperspectral image (HSI) cube can be naturally represented as a third-ord…