2022
DOI: 10.1016/j.saa.2021.120533
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Hierarchical classification models and Handheld NIR spectrometer to human blood stains identification on different floor tiles

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Cited by 9 publications
(16 citation statements)
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“…The hierarchical classication models were built in the same way as has been detailed in the previous work. 7 Data analysis and pre-processing All data were analysed using MATLAB (R2010a 7.10.0.499, MathWorks) and the hierarchical models, SIMCA and PLS-DA models were built using PLS_Toolbox (Eigenvector Research, Inc.). Following the procedure described by Fonseca et al, 7 the spectra of all the samples were cut to the 1000-1600 nm range due to the presence of noise or other physical effects observed previously for this equipment with this type of sample.…”
Section: Spectral Collectionmentioning
confidence: 99%
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“…The hierarchical classication models were built in the same way as has been detailed in the previous work. 7 Data analysis and pre-processing All data were analysed using MATLAB (R2010a 7.10.0.499, MathWorks) and the hierarchical models, SIMCA and PLS-DA models were built using PLS_Toolbox (Eigenvector Research, Inc.). Following the procedure described by Fonseca et al, 7 the spectra of all the samples were cut to the 1000-1600 nm range due to the presence of noise or other physical effects observed previously for this equipment with this type of sample.…”
Section: Spectral Collectionmentioning
confidence: 99%
“…7 Data analysis and pre-processing All data were analysed using MATLAB (R2010a 7.10.0.499, MathWorks) and the hierarchical models, SIMCA and PLS-DA models were built using PLS_Toolbox (Eigenvector Research, Inc.). Following the procedure described by Fonseca et al, 7 the spectra of all the samples were cut to the 1000-1600 nm range due to the presence of noise or other physical effects observed previously for this equipment with this type of sample. Savitzky Golay 1st Derivative technique with 15 smoothing points and a 2nd degree polynomial was used with all the data.…”
Section: Spectral Collectionmentioning
confidence: 99%
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