Matches in SemOpenAlex for { <https://semopenalex.org/work/W3014247029> ?p ?o ?g. }
- W3014247029 endingPage "87" @default.
- W3014247029 startingPage "70" @default.
- W3014247029 abstract "Existing robust non-negative matrix factorization methods fail to achieve data recovery and learn a robust representation. This is because these methods suppose that outliers and noise of the original data are the Gaussian distribution . In this paper, we propose a robust non-negative matrix model , called robust Manhattan non-negative matrix factorization, which can handle various noise (e.g. Gaussian noise , Salt and Pepper noise or Contiguous Occlusion). Different from previous robust non-negative matrix factorization models , we utilize mean filter and matrix completion as additional constraints to recover the corrupted data from normal data or neighbouring corrupted data, and achieve a robust low-dimensional representation by Manhattan non-negative matrix factorization. We theoretically compare the robustness of our proposed model with other non-negative matrix factorization models and theoretically prove the effectiveness of the proposed algorithm. Extensive experimental results on the image dataset containing noise and outliers validate the robustness and effectiveness of our proposed model for image recovery and representation." @default.
- W3014247029 created "2020-04-10" @default.
- W3014247029 creator A5000100573 @default.
- W3014247029 creator A5014126274 @default.
- W3014247029 creator A5029065444 @default.
- W3014247029 creator A5053561890 @default.
- W3014247029 creator A5076699095 @default.
- W3014247029 date "2020-07-01" @default.
- W3014247029 modified "2023-10-16" @default.
- W3014247029 title "Robust Manhattan non-negative matrix factorization for image recovery and representation" @default.
- W3014247029 cites W1902027874 @default.
- W3014247029 cites W1919585499 @default.
- W3014247029 cites W1969698720 @default.
- W3014247029 cites W1972292376 @default.
- W3014247029 cites W1976645892 @default.
- W3014247029 cites W2021954339 @default.
- W3014247029 cites W2026034143 @default.
- W3014247029 cites W2054090515 @default.
- W3014247029 cites W2084983808 @default.
- W3014247029 cites W2089088255 @default.
- W3014247029 cites W2104819583 @default.
- W3014247029 cites W2110096996 @default.
- W3014247029 cites W2114968688 @default.
- W3014247029 cites W2118375674 @default.
- W3014247029 cites W2144730066 @default.
- W3014247029 cites W2167732364 @default.
- W3014247029 cites W2169658215 @default.
- W3014247029 cites W2344878508 @default.
- W3014247029 cites W2364980675 @default.
- W3014247029 cites W2557489574 @default.
- W3014247029 cites W2607323999 @default.
- W3014247029 cites W2611328865 @default.
- W3014247029 cites W2612356425 @default.
- W3014247029 cites W2783594155 @default.
- W3014247029 cites W2804176448 @default.
- W3014247029 cites W2804454015 @default.
- W3014247029 cites W2830365116 @default.
- W3014247029 cites W2903254834 @default.
- W3014247029 cites W2906898454 @default.
- W3014247029 cites W2923396414 @default.
- W3014247029 cites W2935791181 @default.
- W3014247029 cites W2970503027 @default.
- W3014247029 cites W3106158395 @default.
- W3014247029 cites W3124114587 @default.
- W3014247029 doi "https://doi.org/10.1016/j.ins.2020.03.096" @default.
- W3014247029 hasPublicationYear "2020" @default.
- W3014247029 type Work @default.
- W3014247029 sameAs 3014247029 @default.
- W3014247029 citedByCount "14" @default.
- W3014247029 countsByYear W30142470292020 @default.
- W3014247029 countsByYear W30142470292021 @default.
- W3014247029 countsByYear W30142470292022 @default.
- W3014247029 countsByYear W30142470292023 @default.
- W3014247029 crossrefType "journal-article" @default.
- W3014247029 hasAuthorship W3014247029A5000100573 @default.
- W3014247029 hasAuthorship W3014247029A5014126274 @default.
- W3014247029 hasAuthorship W3014247029A5029065444 @default.
- W3014247029 hasAuthorship W3014247029A5053561890 @default.
- W3014247029 hasAuthorship W3014247029A5076699095 @default.
- W3014247029 hasConcept C104317684 @default.
- W3014247029 hasConcept C11413529 @default.
- W3014247029 hasConcept C121332964 @default.
- W3014247029 hasConcept C152671427 @default.
- W3014247029 hasConcept C153180895 @default.
- W3014247029 hasConcept C154945302 @default.
- W3014247029 hasConcept C158693339 @default.
- W3014247029 hasConcept C185592680 @default.
- W3014247029 hasConcept C187834632 @default.
- W3014247029 hasConcept C33923547 @default.
- W3014247029 hasConcept C41008148 @default.
- W3014247029 hasConcept C4199805 @default.
- W3014247029 hasConcept C42355184 @default.
- W3014247029 hasConcept C55493867 @default.
- W3014247029 hasConcept C62520636 @default.
- W3014247029 hasConcept C63479239 @default.
- W3014247029 hasConcept C79337645 @default.
- W3014247029 hasConceptScore W3014247029C104317684 @default.
- W3014247029 hasConceptScore W3014247029C11413529 @default.
- W3014247029 hasConceptScore W3014247029C121332964 @default.
- W3014247029 hasConceptScore W3014247029C152671427 @default.
- W3014247029 hasConceptScore W3014247029C153180895 @default.
- W3014247029 hasConceptScore W3014247029C154945302 @default.
- W3014247029 hasConceptScore W3014247029C158693339 @default.
- W3014247029 hasConceptScore W3014247029C185592680 @default.
- W3014247029 hasConceptScore W3014247029C187834632 @default.
- W3014247029 hasConceptScore W3014247029C33923547 @default.
- W3014247029 hasConceptScore W3014247029C41008148 @default.
- W3014247029 hasConceptScore W3014247029C4199805 @default.
- W3014247029 hasConceptScore W3014247029C42355184 @default.
- W3014247029 hasConceptScore W3014247029C55493867 @default.
- W3014247029 hasConceptScore W3014247029C62520636 @default.
- W3014247029 hasConceptScore W3014247029C63479239 @default.
- W3014247029 hasConceptScore W3014247029C79337645 @default.
- W3014247029 hasFunder F4320323172 @default.
- W3014247029 hasFunder F4320324805 @default.
- W3014247029 hasLocation W30142470291 @default.
- W3014247029 hasOpenAccess W3014247029 @default.
- W3014247029 hasPrimaryLocation W30142470291 @default.