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 …
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
Hyperspectral unmixing based on nonnegative matrix factorization: A comprehensive review
Hyperspectral unmixing has been an important technique that estimates a set of
endmembers and their corresponding abundances from a hyperspectral image (HSI) …
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 …
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
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 …
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 …
as a combination of a set of spectral signatures called endmembers and simultaneously …
Spectral variability in hyperspectral data unmixing: A comprehensive review
The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …
Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous
field view in hundreds or thousands of spectral channels with higher spectral resolution than …
field view in hundreds or thousands of spectral channels with higher spectral resolution than …
Hyperspectral unmixing using transformer network
Transformers have intrigued the vision research community with their state-of-the-art
performance in natural language processing. With their superior performance, transformers …
performance in natural language processing. With their superior performance, transformers …
uDAS: An untied denoising autoencoder with sparsity for spectral unmixing
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 …
combination of the constituent endmembers and the estimated abundances. This paper …
UnDIP: Hyperspectral unmixing using deep image prior
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 …
unmixing problem. The proposed method contains two main steps. First, the endmembers …