Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM).
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Classification of Camellia (Theaceae) species using leaf architecture variations and pattern recognition techniquesAdvanced nonlinear approaches for predicting the ingredient composition in compound feedingstuffs by near-infrared reflection spectroscopy.Stable Isotope Ratio and Elemental Profile Combined with Support Vector Machine for Provenance Discrimination of Oolong Tea (Wuyi-Rock Tea).Residues and contaminants in tea and tea infusions: a review.Identification of tea storage times by linear discrimination analysis and back-propagation neural network techniques based on the eigenvalues of principal components analysis of e-nose sensor signalsCombination of the Manifold Dimensionality Reduction Methods with Least Squares Support vector machines for Classifying the Species of Sorghum Seeds.Visible/near infrared spectroscopy and chemometrics for the prediction of trace element (Fe and Zn) levels in rice leaf.On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopyStudy on discrimination of white tea and albino tea based on near-infrared spectroscopy and chemometrics.Feature Fusion of ICP-AES, UV-Vis and FT-MIR for Origin Traceability of Boletus edulis Mushrooms in Combination with Chemometrics.Quality Assessment of Gentiana rigescens from Different Geographical Origins Using FT-IR Spectroscopy Combined with HPLC.Simultaneous determination of amino acid nitrogen and total acid in soy sauce using near infrared spectroscopy combined with characteristic variables selection.Pre-visual diagnostics of phosphorus deficiency in mini-cucumber plants using near-infrared reflectance spectroscopy.Characterization of Gentiana rigescens by Ultraviolet–Visible and Infrared Spectroscopies with ChemometricsTea Category Identification Using a Novel Fractional Fourier Entropy and Jaya AlgorithmIdentification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector MachineClassification of Liquor Using Near-Infrared Spectroscopy and ChemometricsNear-Infrared Spectroscopy for Anticounterfeiting Innovative FibersLychee Variety Discrimination by Hyperspectral Imaging Coupled with Multivariate ClassificationMeasurement of Soluble Solid Contents and pH of White Vinegars Using VIS/NIR Spectroscopy and Least Squares Support Vector Machine
P2860
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P2860
Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM).
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh-hant
name
Feasibility study on identific ...... support vector machine (SVM).
@en
Feasibility study on identific ...... support vector machine (SVM).
@nl
type
label
Feasibility study on identific ...... support vector machine (SVM).
@en
Feasibility study on identific ...... support vector machine (SVM).
@nl
prefLabel
Feasibility study on identific ...... support vector machine (SVM).
@en
Feasibility study on identific ...... support vector machine (SVM).
@nl
P2093
P1476
Feasibility study on identific ...... n support vector machine (SVM)
@en
P2093
Dongmei Wang
Jiewen Zhao
P304
P356
10.1016/J.SAA.2006.03.038
P407
P577
2006-04-18T00:00:00Z