Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313554953> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W4313554953 endingPage "4" @default.
- W4313554953 startingPage "1" @default.
- W4313554953 abstract "Because most plastics are incompatible and cannot be blended, polymers must be separated before recycling. We propose a sensor-based classifier that collects NIR wavelengths from polymers to estimate their composition. Unlike prior research, this work aims to apply machine learning to the difficult problem of categorizing low-reflectance black polymers in NIR and without complimentary sensory data. We collected 1491 hyperspectral pictures of roughly 4500 plastic pieces from an industrial recycling operation. Using N-BEATS, an ensemble deep learning approach for waveform decomposition, we achieved an overall f1-score of 0.79 and accuracy of 0.79 for all plastics, 0.9 for colored plastics, and 0.67 for black plastics. The method achieves noteworthy performance results, as black polymer differentiation in the NIR has been deemed unfeasible by the majority of the existing literature." @default.
- W4313554953 created "2023-01-06" @default.
- W4313554953 creator A5005581980 @default.
- W4313554953 creator A5006244516 @default.
- W4313554953 creator A5042827312 @default.
- W4313554953 creator A5062544622 @default.
- W4313554953 creator A5072126417 @default.
- W4313554953 creator A5080205457 @default.
- W4313554953 date "2023-01-01" @default.
- W4313554953 modified "2023-09-30" @default.
- W4313554953 title "Plastic Classification With NIR Hyperspectral Images and Deep Learning" @default.
- W4313554953 cites W1991413263 @default.
- W4313554953 cites W2014872549 @default.
- W4313554953 cites W2057449738 @default.
- W4313554953 cites W2256424214 @default.
- W4313554953 cites W2507416357 @default.
- W4313554953 cites W2599734259 @default.
- W4313554953 cites W2739166259 @default.
- W4313554953 cites W2912398024 @default.
- W4313554953 cites W2936503027 @default.
- W4313554953 cites W2979714976 @default.
- W4313554953 cites W2998702515 @default.
- W4313554953 cites W3124509338 @default.
- W4313554953 cites W3127336758 @default.
- W4313554953 cites W4293256647 @default.
- W4313554953 cites W4293770534 @default.
- W4313554953 doi "https://doi.org/10.1109/lsens.2023.3234401" @default.
- W4313554953 hasPublicationYear "2023" @default.
- W4313554953 type Work @default.
- W4313554953 citedByCount "2" @default.
- W4313554953 countsByYear W43135549532023 @default.
- W4313554953 crossrefType "journal-article" @default.
- W4313554953 hasAuthorship W4313554953A5005581980 @default.
- W4313554953 hasAuthorship W4313554953A5006244516 @default.
- W4313554953 hasAuthorship W4313554953A5042827312 @default.
- W4313554953 hasAuthorship W4313554953A5062544622 @default.
- W4313554953 hasAuthorship W4313554953A5072126417 @default.
- W4313554953 hasAuthorship W4313554953A5080205457 @default.
- W4313554953 hasConcept C108583219 @default.
- W4313554953 hasConcept C108597893 @default.
- W4313554953 hasConcept C120665830 @default.
- W4313554953 hasConcept C121332964 @default.
- W4313554953 hasConcept C153180895 @default.
- W4313554953 hasConcept C154945302 @default.
- W4313554953 hasConcept C159078339 @default.
- W4313554953 hasConcept C159985019 @default.
- W4313554953 hasConcept C192562407 @default.
- W4313554953 hasConcept C2778307483 @default.
- W4313554953 hasConcept C39432304 @default.
- W4313554953 hasConcept C41008148 @default.
- W4313554953 hasConcept C49040817 @default.
- W4313554953 hasConcept C521977710 @default.
- W4313554953 hasConcept C6260449 @default.
- W4313554953 hasConcept C95623464 @default.
- W4313554953 hasConceptScore W4313554953C108583219 @default.
- W4313554953 hasConceptScore W4313554953C108597893 @default.
- W4313554953 hasConceptScore W4313554953C120665830 @default.
- W4313554953 hasConceptScore W4313554953C121332964 @default.
- W4313554953 hasConceptScore W4313554953C153180895 @default.
- W4313554953 hasConceptScore W4313554953C154945302 @default.
- W4313554953 hasConceptScore W4313554953C159078339 @default.
- W4313554953 hasConceptScore W4313554953C159985019 @default.
- W4313554953 hasConceptScore W4313554953C192562407 @default.
- W4313554953 hasConceptScore W4313554953C2778307483 @default.
- W4313554953 hasConceptScore W4313554953C39432304 @default.
- W4313554953 hasConceptScore W4313554953C41008148 @default.
- W4313554953 hasConceptScore W4313554953C49040817 @default.
- W4313554953 hasConceptScore W4313554953C521977710 @default.
- W4313554953 hasConceptScore W4313554953C6260449 @default.
- W4313554953 hasConceptScore W4313554953C95623464 @default.
- W4313554953 hasIssue "1" @default.
- W4313554953 hasLocation W43135549531 @default.
- W4313554953 hasOpenAccess W4313554953 @default.
- W4313554953 hasPrimaryLocation W43135549531 @default.
- W4313554953 hasRelatedWork W2028628118 @default.
- W4313554953 hasRelatedWork W2563096758 @default.
- W4313554953 hasRelatedWork W2597241479 @default.
- W4313554953 hasRelatedWork W2807839383 @default.
- W4313554953 hasRelatedWork W2899084033 @default.
- W4313554953 hasRelatedWork W2921350538 @default.
- W4313554953 hasRelatedWork W3173596272 @default.
- W4313554953 hasRelatedWork W4291701050 @default.
- W4313554953 hasRelatedWork W4312789307 @default.
- W4313554953 hasRelatedWork W3158004940 @default.
- W4313554953 hasVolume "7" @default.
- W4313554953 isParatext "false" @default.
- W4313554953 isRetracted "false" @default.
- W4313554953 workType "article" @default.