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Performance of A Statistical-Based Automatic Contrast-to-Noise Ratio Measurement on Images of the ACR CT Phantom. [PDF]

J Imaging
Anam C, Amilia R, Naufal A, Sutanto H, Budi WS, Dougherty G.   +5 more
europepmc   +1 more source

Combination of machine learning and Raman spectroscopy for prediction of drug release in targeted drug delivery formulations. [PDF]

Sci Rep
Mahdi WA, Alhowyan A, Obaidullah AJ.
europepmc   +1 more source

Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. [PDF]

PLoS One
Long Y.
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PAL - parallel active learning for machine-learned potentials.

Digit Discov
Zhou C, Neubert M, Koide Y, Zhang Y, Vuong VQ, Schlöder T, Dehnen S, Friederich P.   +7 more
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Evaluation of Matrix Effects in SIMS Using Gaussian Process Regression: The Case of Olivine Mg Isotope Microanalysis. [PDF]

Rapid Commun Mass Spectrom
Itano K, Fukuda K, Kita NT, Ueki K, Kuwatani T, Akaho S.   +5 more
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Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification. [PDF]

J Chem Theory Comput
Mollaei P, Barati Farimani A.
europepmc   +1 more source

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Low Rank Component Induced Spatial-Spectral Kernel Method for Hyperspectral Image Classification

IEEE transactions on circuits and systems for video technology (Print), 2020
Kernel methods, e.g., composite kernels (CKs) and spatial-spectral kernels (SSKs), have been demonstrated to be an effective way to exploit the spatial-spectral information nonlinearly for improving the classification performance of hyperspectral image ...
Le Sun, Chenyan Ma, Yunjie Chen, Yuhui Zheng, H. Shim, Zebin Wu, B. Jeon   +6 more
semanticscholar   +1 more source