Abstract: In this work, we modeled a novel approach to enhance surface-enhanced Raman scattering (SERS) signals using principal component analysis (PCA) as a machine learning approach. Zinc oxide ...
Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, College of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, China. With the ...
Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, graphical clustering, and ...
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SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery
Abstract: As an unsupervised dimensionality reduction method, the principal component analysis (PCA) has been widely considered as an efficient and effective preprocessing step for hyperspectral image ...
A growing number of studies apply Principal Component Analysis (PCA) on whole-body kinematic data to facilitate an analysis of posture changes in human movement. An unanswered question is, how much ...
Chemical contaminants are frequently found in mixtures of similar molecules; their identification typically starts with time-consuming separation steps prior to identification of individual components ...
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