Machine learning for quantum matter

J Carrasquilla - Advances in Physics: X, 2020 - Taylor & Francis
Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …

Hyperspectral unmixing based on nonnegative matrix factorization: A comprehensive review

XR Feng, HC Li, R Wang, Q Du, X Jia… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …

[PDF][PDF] 中国高光谱遥感的前沿进展

童庆禧, 张兵, 张立福 - 遥感学报, 2016 - hrs-cas.com
高光谱成像技术具有光谱分辨率高, 图谱合一的独特优势, 是遥感技术发展以来最重大的科技
突破之一. 中国的高光谱遥感发展与国际基本同步, 在国家和省部级科研项目的支持下 …

DAEN: Deep autoencoder networks for hyperspectral unmixing

Y Su, J Li, A Plaza, A Marinoni, P Gamba… - … on Geoscience and …, 2019 - ieeexplore.ieee.org
Spectral unmixing is a technique for remotely sensed image interpretation that expresses
each (possibly mixed) pixel as a combination of pure spectral signatures (endmembers) and …

Convolutional autoencoder for spectral–spatial hyperspectral unmixing

B Palsson, MO Ulfarsson… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Blind hyperspectral unmixing is the process of expressing the measured spectrum of a pixel
as a combination of a set of spectral signatures called endmembers and simultaneously …

Spectral variability in hyperspectral data unmixing: A comprehensive review

RA Borsoi, T Imbiriba, JCM Bermudez… - … and remote sensing …, 2021 - ieeexplore.ieee.org
The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches

JM Bioucas-Dias, A Plaza, N Dobigeon… - IEEE journal of …, 2012 - ieeexplore.ieee.org
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …

Hyperspectral unmixing using transformer network

P Ghosh, SK Roy, B Koirala, B Rasti… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Transformers have intrigued the vision research community with their state-of-the-art
performance in natural language processing. With their superior performance, transformers …

uDAS: An untied denoising autoencoder with sparsity for spectral unmixing

Y Qu, H Qi - IEEE Transactions on Geoscience and Remote …, 2018 - ieeexplore.ieee.org
Linear spectral unmixing is the practice of decomposing the mixed pixel into a linear
combination of the constituent endmembers and the estimated abundances. This paper …

UnDIP: Hyperspectral unmixing using deep image prior

B Rasti, B Koirala, P Scheunders… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, we introduce a deep learning-based technique for the linear hyperspectral
unmixing problem. The proposed method contains two main steps. First, the endmembers …