Matches in SemOpenAlex for { <https://semopenalex.org/work/W2583925103> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2583925103 endingPage "166" @default.
- W2583925103 startingPage "158" @default.
- W2583925103 abstract "Abstract In this paper, we investigate the effectiveness of two-stage classification strategies in detecting north Atlantic right whale upcalls. Time-frequency measurements of data from passive acoustic monitoring devices are evaluated as images. Vocalization spectrograms are preprocessed for noise reduction and tone removal. First stage of the algorithm eliminates non-upcalls by an energy detection algorithm. In the second stage, two sets of features are extracted from the remaining signals using contour-based and texture based methods. The former is based on extraction of time–frequency features from upcall contours, and the latter employs a Local Binary Pattern operator to extract distinguishing texture features of the upcalls. Subsequently evaluation phase is carried out by using several classifiers to assess the effectiveness of both the contour-based and texture-based features for upcall detection. Comparing ROC curves of machine learning algorithms obtained from Cornell University’s dataset reveals that LBP features improved performance accuracy up to 43% over time–frequency features. Classifiers such as the Linear Discriminant Analysis, Support Vector Machine, and TreeBagger achieve highest upcall detection rates with LBP features." @default.
- W2583925103 created "2017-02-10" @default.
- W2583925103 creator A5026298167 @default.
- W2583925103 creator A5063333321 @default.
- W2583925103 creator A5074069054 @default.
- W2583925103 creator A5085936112 @default.
- W2583925103 date "2017-05-01" @default.
- W2583925103 modified "2023-10-17" @default.
- W2583925103 title "Two-stage detection of north Atlantic right whale upcalls using local binary patterns and machine learning algorithms" @default.
- W2583925103 cites W1507018650 @default.
- W2583925103 cites W1967619747 @default.
- W2583925103 cites W1968415887 @default.
- W2583925103 cites W1974055562 @default.
- W2583925103 cites W1989474456 @default.
- W2583925103 cites W2030638838 @default.
- W2583925103 cites W2039051707 @default.
- W2583925103 cites W2043741560 @default.
- W2583925103 cites W2046729446 @default.
- W2583925103 cites W2052129642 @default.
- W2583925103 cites W2053188693 @default.
- W2583925103 cites W2066629230 @default.
- W2583925103 cites W2089973461 @default.
- W2583925103 cites W2153814531 @default.
- W2583925103 cites W4239510810 @default.
- W2583925103 doi "https://doi.org/10.1016/j.apacoust.2017.01.025" @default.
- W2583925103 hasPublicationYear "2017" @default.
- W2583925103 type Work @default.
- W2583925103 sameAs 2583925103 @default.
- W2583925103 citedByCount "8" @default.
- W2583925103 countsByYear W25839251032017 @default.
- W2583925103 countsByYear W25839251032020 @default.
- W2583925103 countsByYear W25839251032022 @default.
- W2583925103 crossrefType "journal-article" @default.
- W2583925103 hasAuthorship W2583925103A5026298167 @default.
- W2583925103 hasAuthorship W2583925103A5063333321 @default.
- W2583925103 hasAuthorship W2583925103A5074069054 @default.
- W2583925103 hasAuthorship W2583925103A5085936112 @default.
- W2583925103 hasConcept C11413529 @default.
- W2583925103 hasConcept C115961682 @default.
- W2583925103 hasConcept C127313418 @default.
- W2583925103 hasConcept C146357865 @default.
- W2583925103 hasConcept C151730666 @default.
- W2583925103 hasConcept C153180895 @default.
- W2583925103 hasConcept C154945302 @default.
- W2583925103 hasConcept C2776088427 @default.
- W2583925103 hasConcept C2776224462 @default.
- W2583925103 hasConcept C2777704720 @default.
- W2583925103 hasConcept C33923547 @default.
- W2583925103 hasConcept C41008148 @default.
- W2583925103 hasConcept C48372109 @default.
- W2583925103 hasConcept C505870484 @default.
- W2583925103 hasConcept C53533937 @default.
- W2583925103 hasConcept C86803240 @default.
- W2583925103 hasConcept C87335442 @default.
- W2583925103 hasConcept C94375191 @default.
- W2583925103 hasConceptScore W2583925103C11413529 @default.
- W2583925103 hasConceptScore W2583925103C115961682 @default.
- W2583925103 hasConceptScore W2583925103C127313418 @default.
- W2583925103 hasConceptScore W2583925103C146357865 @default.
- W2583925103 hasConceptScore W2583925103C151730666 @default.
- W2583925103 hasConceptScore W2583925103C153180895 @default.
- W2583925103 hasConceptScore W2583925103C154945302 @default.
- W2583925103 hasConceptScore W2583925103C2776088427 @default.
- W2583925103 hasConceptScore W2583925103C2776224462 @default.
- W2583925103 hasConceptScore W2583925103C2777704720 @default.
- W2583925103 hasConceptScore W2583925103C33923547 @default.
- W2583925103 hasConceptScore W2583925103C41008148 @default.
- W2583925103 hasConceptScore W2583925103C48372109 @default.
- W2583925103 hasConceptScore W2583925103C505870484 @default.
- W2583925103 hasConceptScore W2583925103C53533937 @default.
- W2583925103 hasConceptScore W2583925103C86803240 @default.
- W2583925103 hasConceptScore W2583925103C87335442 @default.
- W2583925103 hasConceptScore W2583925103C94375191 @default.
- W2583925103 hasLocation W25839251031 @default.
- W2583925103 hasOpenAccess W2583925103 @default.
- W2583925103 hasPrimaryLocation W25839251031 @default.
- W2583925103 hasRelatedWork W2085553065 @default.
- W2583925103 hasRelatedWork W2092714610 @default.
- W2583925103 hasRelatedWork W2122718025 @default.
- W2583925103 hasRelatedWork W2404514746 @default.
- W2583925103 hasRelatedWork W2583925103 @default.
- W2583925103 hasRelatedWork W2597305757 @default.
- W2583925103 hasRelatedWork W2900460335 @default.
- W2583925103 hasRelatedWork W4288057579 @default.
- W2583925103 hasRelatedWork W2181817726 @default.
- W2583925103 hasRelatedWork W2342684998 @default.
- W2583925103 hasVolume "120" @default.
- W2583925103 isParatext "false" @default.
- W2583925103 isRetracted "false" @default.
- W2583925103 magId "2583925103" @default.
- W2583925103 workType "article" @default.