Results 111 to 120 of about 919,951 (170)

Efficient Progressive Mamba Model for Hyperspectral Sequence Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, deep learning-based hyperspectral unmixing has increasingly incorporated spatial information to improve performance. However, the extent of spatial information introduced involves a complex tradeoff: too little offers limited gains ...
Yang Liu, Shujun Liu, Huajun Wang
doaj   +1 more source

Hyperspectral Unmixing Using Frequency-Adaptive Convolutional-Mamba Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, deep learning (DL) has achieved remarkable progress in hyperspectral unmixing (HU) owing to its powerful feature extraction and modeling capabilities.
Zhuoyi Zhao, Xiang Xu, Chuiyi Deng, Yanyin Guo, Junwei Li, Antonio Plaza   +5 more
doaj   +1 more source

Diffusion Model Based Hyperspectral Unmixing Using Spectral Prior Distribution

Hyperspectral unmixing is a crucial task for identifying the constituent materials and their respective distributions in a scene. Utilizing known spectral libraries as prior information, semi-blind unmixing methods (also known as spectral-library-based ...
Qian, Yuntao, Zhou, Jun, Deng, Keli, Nie, Jie   +3 more
core   +1 more source

Hypergraph Higher Order Association and Collaborative Interactive Attention Network for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing (HU) aims to extract the pure material spectra (endmember) and their corresponding fractions (abundances) from the mixed pixels.
Kewen Qu, Hao Wu, Chunneng Yang, Yuwei Wang, Wenxing Bao   +4 more
doaj   +1 more source

A Two-Stage Decoupling Framework for Blind Hyperspectral Unmixing: Separately Refining Endmembers and Abundances

Remote Sensing
Hyperspectral unmixing (HU) aims to estimate endmembers and their corresponding abundances, a task commonly referred to as blind hyperspectral unmixing (BLU). Nonnegative matrix factorization (NMF) provides a unified framework for their joint estimation.
Hengnuo Liu, Yulin Zhang, Yanyan Li, Yongli Wang, Xiuchuan Chen   +4 more
doaj   +1 more source

A Fast Sparse NMF Optimization Algorithm for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral remote sensing images have received extensive attention because of their high spectral resolution. However, the limitation of spatial resolution of imaging spectrometers results in a large number of mixed pixels, which restricts the ...
Kewen Qu, Zhenqing Li
doaj   +1 more source

In situ detection of water on the Moon by the Chang'E-5 lander. [PDF]

Sci Adv, 2022
Lin H, Li S, Xu R, Liu Y, Wu X, Yang W, Wei Y, Lin Y, He Z, Hui H, He H, Hu S, Zhang C, Li C, Lv G, Yuan L, Zou Y, Wang C.   +17 more
europepmc   +1 more source

Transformer for Multitemporal Hyperspectral Image Unmixing [PDF]

Multitemporal hyperspectral image unmixing (MTHU) holds significant importance in monitoring and analyzing the dynamic changes of surface. However, compared to single-temporal unmixing, the multitemporal approach demands comprehensive consideration of ...
Li, Hang, Li, Tao, Xu, Xia, Dong, Qiankun, Shi, Zhenwei, Xie, Xueshuo   +5 more
core   +1 more source

3D Polymer Architectures for the Identification of Optimal Dimensions for Cellular Growth of 3D Cellular Models. [PDF]

Polymers (Basel), 2022
Maibohm C, Saldana-Lopez A, Silvestre OF, Nieder JB.   +3 more
europepmc   +1 more source

Spatial sterol metabolism unveiled by stimulated Raman imaging. [PDF]

Front Chem, 2023
Zhang Y, Zhou Y, Fang W, Zhu H, Ye C, Zhang D, Lee HJ.   +6 more
europepmc   +1 more source