Matches in SemOpenAlex for { <https://semopenalex.org/work/W4382073721> ?p ?o ?g. }
- W4382073721 endingPage "165138" @default.
- W4382073721 startingPage "165138" @default.
- W4382073721 abstract "With the increasing interest in microplastics (MPs) pollutants, relevant detection technologies are also developing. In MPs analysis, vibrational spectroscopy represented by surface-enhanced Raman spectroscopy (SERS) is widely used because they can provide unique fingerprint characteristics of chemical components. However, it is still a challenge to separate various chemical components from the SERS spectra of MPs mixture. In this study, it is innovatively proposed to combine the convolutional neural networks (CNN) model to simultaneously identify and analyze each component in the SERS spectra of six common MPs mixture. Different from the traditional method, which requires a series of spectral preprocessing such as baseline correction, smoothing and filtering, the average identification accuracy of MP components is as high as 99.54 % after the unpreprocessed spectral data is trained by CNN, which is better than other classical algorithms such as support vector machine (SVM), principal component analysis linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA), Random Forest (RF), and K Near Neighbor (KNN), with or without spectral preprocessing. The high accuracy shows that CNN can be used to quickly identify MPs mixture with unpreprocessed SERS spectra data." @default.
- W4382073721 created "2023-06-27" @default.
- W4382073721 creator A5017116428 @default.
- W4382073721 creator A5022859981 @default.
- W4382073721 creator A5031898723 @default.
- W4382073721 creator A5044179485 @default.
- W4382073721 creator A5057994349 @default.
- W4382073721 creator A5058843083 @default.
- W4382073721 creator A5076947773 @default.
- W4382073721 date "2023-10-01" @default.
- W4382073721 modified "2023-10-16" @default.
- W4382073721 title "Component identification for the SERS spectra of microplastics mixture with convolutional neural network" @default.
- W4382073721 cites W2188592721 @default.
- W4382073721 cites W2399847652 @default.
- W4382073721 cites W2528340666 @default.
- W4382073721 cites W2552801592 @default.
- W4382073721 cites W2606658292 @default.
- W4382073721 cites W2789904487 @default.
- W4382073721 cites W2969280700 @default.
- W4382073721 cites W2972050955 @default.
- W4382073721 cites W2983689288 @default.
- W4382073721 cites W3019241137 @default.
- W4382073721 cites W3033001421 @default.
- W4382073721 cites W3035360512 @default.
- W4382073721 cites W3042891209 @default.
- W4382073721 cites W3045070191 @default.
- W4382073721 cites W3046294912 @default.
- W4382073721 cites W3080198602 @default.
- W4382073721 cites W3087710342 @default.
- W4382073721 cites W3093704141 @default.
- W4382073721 cites W3097318511 @default.
- W4382073721 cites W3098911958 @default.
- W4382073721 cites W3112507989 @default.
- W4382073721 cites W3114399463 @default.
- W4382073721 cites W3126538505 @default.
- W4382073721 cites W3173476859 @default.
- W4382073721 cites W3185453697 @default.
- W4382073721 cites W3194879961 @default.
- W4382073721 cites W3196128465 @default.
- W4382073721 cites W3204383904 @default.
- W4382073721 cites W3206977973 @default.
- W4382073721 cites W3209845491 @default.
- W4382073721 cites W4220655782 @default.
- W4382073721 cites W4226020605 @default.
- W4382073721 cites W4293770534 @default.
- W4382073721 cites W4295592553 @default.
- W4382073721 cites W4310048683 @default.
- W4382073721 cites W4311421434 @default.
- W4382073721 cites W4311512918 @default.
- W4382073721 cites W4367397067 @default.
- W4382073721 doi "https://doi.org/10.1016/j.scitotenv.2023.165138" @default.
- W4382073721 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37379925" @default.
- W4382073721 hasPublicationYear "2023" @default.
- W4382073721 type Work @default.
- W4382073721 citedByCount "1" @default.
- W4382073721 countsByYear W43820737212023 @default.
- W4382073721 crossrefType "journal-article" @default.
- W4382073721 hasAuthorship W4382073721A5017116428 @default.
- W4382073721 hasAuthorship W4382073721A5022859981 @default.
- W4382073721 hasAuthorship W4382073721A5031898723 @default.
- W4382073721 hasAuthorship W4382073721A5044179485 @default.
- W4382073721 hasAuthorship W4382073721A5057994349 @default.
- W4382073721 hasAuthorship W4382073721A5058843083 @default.
- W4382073721 hasAuthorship W4382073721A5076947773 @default.
- W4382073721 hasConcept C116834253 @default.
- W4382073721 hasConcept C119857082 @default.
- W4382073721 hasConcept C12267149 @default.
- W4382073721 hasConcept C127313418 @default.
- W4382073721 hasConcept C153180895 @default.
- W4382073721 hasConcept C154945302 @default.
- W4382073721 hasConcept C176641082 @default.
- W4382073721 hasConcept C186060115 @default.
- W4382073721 hasConcept C22354355 @default.
- W4382073721 hasConcept C27438332 @default.
- W4382073721 hasConcept C31972630 @default.
- W4382073721 hasConcept C34736171 @default.
- W4382073721 hasConcept C3770464 @default.
- W4382073721 hasConcept C41008148 @default.
- W4382073721 hasConcept C59822182 @default.
- W4382073721 hasConcept C62649853 @default.
- W4382073721 hasConcept C69738355 @default.
- W4382073721 hasConcept C81363708 @default.
- W4382073721 hasConcept C86803240 @default.
- W4382073721 hasConceptScore W4382073721C116834253 @default.
- W4382073721 hasConceptScore W4382073721C119857082 @default.
- W4382073721 hasConceptScore W4382073721C12267149 @default.
- W4382073721 hasConceptScore W4382073721C127313418 @default.
- W4382073721 hasConceptScore W4382073721C153180895 @default.
- W4382073721 hasConceptScore W4382073721C154945302 @default.
- W4382073721 hasConceptScore W4382073721C176641082 @default.
- W4382073721 hasConceptScore W4382073721C186060115 @default.
- W4382073721 hasConceptScore W4382073721C22354355 @default.
- W4382073721 hasConceptScore W4382073721C27438332 @default.
- W4382073721 hasConceptScore W4382073721C31972630 @default.
- W4382073721 hasConceptScore W4382073721C34736171 @default.
- W4382073721 hasConceptScore W4382073721C3770464 @default.
- W4382073721 hasConceptScore W4382073721C41008148 @default.
- W4382073721 hasConceptScore W4382073721C59822182 @default.