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MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

 
dc.contributor.authorRasti, Behnood
dc.contributor.authorKoirala, Bikram
dc.contributor.authorScheunders, Paul
dc.contributor.authorChanussot, Jocelyn
dc.contributor.imecauthorKoirala, Bikram
dc.contributor.imecauthorScheunders, Paul
dc.contributor.orcidimecKoirala, Bikram::0000-0002-8887-8197
dc.contributor.orcidimecScheunders, Paul::0000-0003-2447-4772
dc.date.accessioned2022-11-29T10:56:02Z
dc.date.available2022-04-04T02:09:12Z
dc.date.available2022-11-29T10:56:02Z
dc.date.issued2022
dc.description.wosFundingTextThe work of Behnood Rasti was supported by the Alexander-von-Humboldt-Stiftung/Foundation. The work of Bikram Koirala was supported by the Belgian Science Policy Office (BELSPO) in the frame of the STEREO III Programme under Project GEOMIX (SR/06/357).
dc.identifier.doi10.1109/TGRS.2022.3146904
dc.identifier.issn0196-2892
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/39577
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.beginpage5522815
dc.source.endpagena
dc.source.issuena
dc.source.journalIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
dc.source.numberofpages15
dc.source.volume60
dc.subject.keywordsMATRIX FACTORIZATION
dc.subject.keywordsENDMEMBER EXTRACTION
dc.subject.keywordsSPARSE REGRESSION
dc.subject.keywordsALGORITHM
dc.subject.keywordsREGULARIZATION
dc.subject.keywordsAUTOENCODERS
dc.subject.keywordsIMAGE
dc.title

MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing

dc.typeJournal article
dspace.entity.typePublication
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