Results 101 to 110 of about 265 (159)

Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Framework

This work proposes a variational inference (VI) framework for hyperspectral unmixing in the presence of endmember variability (HU-EV). An EV-accounted noisy linear mixture model (LMM) is considered, and the presence of outliers is also incorporated into ...
Liu, Junbin, Ma, Wing-Kin, Li, Yuening, Fu, Xiao   +3 more
core  

Non-Negative Matrix Factorization with Averaged Kurtosis and Manifold Constraints for Blind Hyperspectral Unmixing

The Nonnegative Matrix Factorization (NMF) algorithm and its variants have gained widespread popularity across various domains, including neural networks, text clustering, image processing, and signal analysis.
Linzhang Lu, Chunli Song, Chengbin Zeng
core   +1 more source

Integration of Raman Spectroscopy and Metabolomics for Early Breast Cancer Detection and Classification. [PDF]

Cancer Med
Li X, Ren H, Deng Y, Li Y, Hu F.
europepmc   +1 more source

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives. [PDF]

Plant Commun, 2022
Tao H, Xu S, Tian Y, Li Z, Ge Y, Zhang J, Wang Y, Zhou G, Deng X, Zhang Z, Ding Y, Jiang D, Guo Q, Jin S.   +13 more
europepmc   +1 more source

In situ secondary structure imaging of protein phase separation and aggregation by hyperspectral stimulated Raman scattering microscopy. [PDF]

Nat Commun
Sun R, Zhuang Y, Lin Y, Hu F.
europepmc   +1 more source

Deep learning-based hyperspectral image correction and unmixing for brain tumor surgery. [PDF]

iScience
Black D, Gill J, Xie A, Liquet B, Di Ieva A, Stummer W, Suero Molina E.   +6 more
europepmc   +1 more source

Tensor Gradient L₀-Norm Minimization-Based Low-Dose CT and Its Application to COVID-19. [PDF]

IEEE Trans Instrum Meas, 2021
Wu W, Shi J, Yu H, Wu W, Vardhanabhuti V.   +4 more
europepmc   +1 more source

Multilayer Simplex-structured Matrix Factorization for Hyperspectral Unmixing with Endmember Variability

Given a hyperspectral image, the problem of hyperspectral unmixing (HU) is to identify the endmembers (or materials) and the abundance (or endmembers' contributions on pixels) that underlie the image. HU can be seen as a matrix factorization problem with
Liu, Junbin, Ma, Wing-Kin, Li, Yuening
core  

Leveraging UAV hyperspectral imaging for crop physiology and biochemistry: A comprehensive review of feature extraction and selection methods. [PDF]

Plant Phenomics
Xu L, Chen L, Luo Q, Zhao S, Huang J, Wang K, Yang Z, Weng X, Fang K, Feng H.   +9 more
europepmc   +1 more source

Niche preclinical and clinical applications of photoacoustic imaging with endogenous contrast. [PDF]

Photoacoustics, 2023
John S, Hester S, Basij M, Paul A, Xavierselvan M, Mehrmohammadi M, Mallidi S.   +6 more
europepmc   +1 more source