Results 51 to 60 of about 6,229 (197)

A Spectral Unmixing Method by Maximum Margin Criterion and Derivative Weights to Address Spectral Variability in Hyperspectral Imagery

Remote Sensing, 2019
Limited to the low spatial resolution of the hyperspectral imaging sensor, mixed pixels are inevitable in hyperspectral images. Therefore, to obtain the endmembers and corresponding fractions in mixed pixels, hyperspectral unmixing becomes a hot spot in ...
Yang Shao, Jinhui Lan
doaj   +1 more source

A New Deep Convolutional Network for Effective Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao, Mercedes E. Paoletti, Lirong Han, Zhaoyue Wu, Peng Ren, Javier Plaza, Antonio Plaza, Juan M. Haut   +7 more
doaj   +1 more source

Fluorescent Diarylethenes With Polar Groups: Synthesis, Spectra, and Optical Microscopy Applications

Chemistry – A European Journal, EarlyView.
Blinking green and flashing red: photo‐switchable and photo‐activatable probes emitting green and red light were prepared and applied as bioconjugates in super‐resolution optical microscopy. ABSTRACT The use of photoactivatable fluorescent diarylethenes (fDAEs) in biology‐related light microscopy has been restricted by the lack of probes having freely ...
Kakishi Uno, Sven Nagorny, Ayse Aktalay, Dojin Kim, Mariano L. Bossi, Vladimir N. Belov, Stefan W. Hell   +6 more
wiley   +1 more source

System-level optimization in spectroscopic photoacoustic imaging of prostate cancer

Photoacoustics, 2022
This study presents a system-level optimization of spectroscopic photoacoustic (PA) imaging for prostate cancer (PCa) detection in three folds. First, we present a spectral unmixing model to segregate spectral system error (SSE). We constructed two noise
Yixuan Wu, Jeeun Kang, Wojciech G. Lesniak, Ala Lisok, Haichong K. Zhang, Russell H. Taylor, Martin G. Pomper, Emad M. Boctor   +7 more
doaj   +1 more source

CompensAID: An Automated Detection Tool for Reference Errors

Cytometry Part A, EarlyView.
ABSTRACT In flow cytometry, raw detector values do not directly represent fluorochrome abundances and must be mathematically unmixed using coefficients derived from single‐stained reference controls. Inaccuracies in these controls, referred to as reference errors, can distort the estimated fluorochrome abundances, leading to skewed population ...
Rosan Olsman, Sarah Bonte, Mattias Hofmans, Malicorne Buysse, Katrien Van der Borght, Yvan Saeys, Vincent H. J. van der Velden, Sofie Van Gassen   +7 more
wiley   +1 more source

Graph-Based Adaptive Network With Spatial-Spectral Features for Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing aims to extract basic material (endmember) spectra and estimate their corresponding fractions (abundances) from observed pixels in hyperspectral images (HSIs).
Hua Dong, Xiaohua Zhang, Jinhua Zhang, Hongyun Meng, Licheng Jiao   +4 more
doaj   +1 more source

eFluor 450 Enables Superior Detection of Intracellular Staphylococcus aureus in High‐Autofluorescence Triple‐Negative Breast Cancer Cells

Cytometry Part A, EarlyView.
ABSTRACT Accurate discrimination of extracellular from intracellular bacteria is critical for assessing microbial invasiveness in host cells. Flow cytometry offers high‐throughput, quantitative analysis but can be confounded by high autofluorescence in certain tumor‐derived cell types.
Sima Kianpour Rad, Runhao Li, Kenny K. L. Yeo, Yoko Tomita, Timothy J. Price, Wendy V. Ingman, Amanda R. Townsend, Eric Smith   +7 more
wiley   +1 more source

Joint Local Block Grouping with Noise-Adjusted Principal Component Analysis for Hyperspectral Remote-Sensing Imagery Sparse Unmixing

Remote Sensing, 2019
Spatial regularized sparse unmixing has been proved as an effective spectral unmixing technique, combining spatial information and standard spectral signatures known in advance into the traditional spectral unmixing model in the form of sparse regression.
Ruyi Feng, Lizhe Wang, Yanfei Zhong
doaj   +1 more source

Superior Intracellular Detection of Cytokines, Transcription Factors, and Phosphoproteins by CyTOF Compared With Fluorescent Cytometry

Cytometry Part A, EarlyView.
ABSTRACT Unraveling biological complexity, such as immune subset distribution in infectious disease(s), autoimmunity, or tumor heterogeneity, requires technologies capable of single‐cell proteomic analysis such as flow cytometry. Surface phenotyping alone is often insufficient, as interrogating functional capacity is required to determine cellular ...
Michael J. Cohen, Erika L. Smith‐Mahoney, Madison Bailey, Ling Wang, Lauren J. Tracey, Laura Polanco, David King, Christina Loh, Amedeo J. Cappione III, Anna C. Belkina, Jennifer E. Snyder‐Cappione   +10 more
wiley   +1 more source

A Global-to-Local Spectral-Spatial Attention-Based Nonlinearity and Scaled Endmember Variability Parametric Learning Network for Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral unmixing has attracted increasing attention in remote sensing applications. Unfortunately, significant unmixing residuals often arise from the coupled nonlinear mixing effects and spectral variability (SV), bringing challenges for reliably ...
Yi Zhao, Bin Yang
doaj   +1 more source