{"id":"https://openalex.org/W2121123096","doi":"https://doi.org/10.1109/tip.2010.2081678","title":"Blind Spectral Unmixing Based on Sparse Nonnegative Matrix Factorization","display_name":"Blind Spectral Unmixing Based on Sparse Nonnegative Matrix Factorization","publication_year":2010,"publication_date":"2010-10-01","ids":{"openalex":"https://openalex.org/W2121123096","doi":"https://doi.org/10.1109/tip.2010.2081678","mag":"2121123096","pmid":"https://pubmed.ncbi.nlm.nih.gov/20889432"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2010.2081678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2010.2081678","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069624559","display_name":"Zuyuan Yang","orcid":"https://orcid.org/0000-0003-2030-707X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuyuan Yang","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China","South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090101808","display_name":"Guoxu Zhou","orcid":"https://orcid.org/0000-0003-1187-577X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxu Zhou","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shengli Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengli Xie","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009582696","display_name":"Shuxue Ding","orcid":"https://orcid.org/0000-0002-4963-3883"},"institutions":[{"id":"https://openalex.org/I141591182","display_name":"University of Aizu","ror":"https://ror.org/02pg0e883","country_code":"JP","type":"education","lineage":["https://openalex.org/I141591182"]},{"id":"https://openalex.org/I2800939219","display_name":"RIKEN Center for Brain Science","ror":"https://ror.org/04j1n1c04","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800939219","https://openalex.org/I4210110652"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shuxue Ding","raw_affiliation_strings":["Brain Science Institute, RIKEN, Saitama, Japan","School of Computer Science and Engineering, University of Aizu, Fukushima, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brain Science Institute, RIKEN, Saitama, Japan","institution_ids":["https://openalex.org/I2800939219"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of Aizu, Fukushima, Japan","institution_ids":["https://openalex.org/I141591182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101795525","display_name":"Junmei Yang","orcid":"https://orcid.org/0000-0002-9677-0768"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun-Mei Yang","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053843140","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0002-0523-5322"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.9256,"has_fulltext":false,"cited_by_count":165,"citation_normalized_percentile":{"value":0.98822592,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"20","issue":"4","first_page":"1112","last_page":"1125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.9168987274169922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6592153310775757},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.6416252255439758},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5856448411941528},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5648032426834106},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.5434210300445557},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5295380353927612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5221691131591797},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5092736482620239},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4736011326313019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4714587330818176},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4488990306854248},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4448358416557312},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41548702120780945},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4121183753013611},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11339259147644043},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.08384069800376892}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.9168987274169922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6592153310775757},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.6416252255439758},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5856448411941528},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5648032426834106},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.5434210300445557},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5295380353927612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5221691131591797},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5092736482620239},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4736011326313019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4714587330818176},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4488990306854248},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4448358416557312},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41548702120780945},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4121183753013611},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11339259147644043},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.08384069800376892},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2010.2081678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2010.2081678","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:20889432","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/20889432","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:dro.deakin.edu.au:DU:30059340","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402457","display_name":"Deakin Research Online (Deakin University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W271314235","https://openalex.org/W1488435683","https://openalex.org/W1514159701","https://openalex.org/W1517170268","https://openalex.org/W1555549210","https://openalex.org/W1582058549","https://openalex.org/W1902027874","https://openalex.org/W1926480693","https://openalex.org/W1976391658","https://openalex.org/W1980988957","https://openalex.org/W1992367803","https://openalex.org/W1993399908","https://openalex.org/W1997146646","https://openalex.org/W2015583498","https://openalex.org/W2017288758","https://openalex.org/W2029251415","https://openalex.org/W2037433057","https://openalex.org/W2046281481","https://openalex.org/W2048393261","https://openalex.org/W2049098239","https://openalex.org/W2056217087","https://openalex.org/W2080486259","https://openalex.org/W2089892215","https://openalex.org/W2092516526","https://openalex.org/W2096673829","https://openalex.org/W2099741732","https://openalex.org/W2100449221","https://openalex.org/W2101837437","https://openalex.org/W2103375047","https://openalex.org/W2105345414","https://openalex.org/W2105454037","https://openalex.org/W2107120407","https://openalex.org/W2111163751","https://openalex.org/W2112229432","https://openalex.org/W2114486983","https://openalex.org/W2114968688","https://openalex.org/W2116793806","https://openalex.org/W2116914769","https://openalex.org/W2118718620","https://openalex.org/W2118943995","https://openalex.org/W2124821796","https://openalex.org/W2127062304","https://openalex.org/W2128090514","https://openalex.org/W2128462828","https://openalex.org/W2131697388","https://openalex.org/W2140086196","https://openalex.org/W2140219630","https://openalex.org/W2144492104","https://openalex.org/W2145554279","https://openalex.org/W2145889472","https://openalex.org/W2146954653","https://openalex.org/W2154332973","https://openalex.org/W2157321686","https://openalex.org/W2160558851","https://openalex.org/W2165755981","https://openalex.org/W2169466597","https://openalex.org/W2295820431","https://openalex.org/W2363685719","https://openalex.org/W2404400936","https://openalex.org/W2998399533","https://openalex.org/W3015755214","https://openalex.org/W3207453635","https://openalex.org/W4233760599","https://openalex.org/W4240046814","https://openalex.org/W6633261909","https://openalex.org/W6634825034","https://openalex.org/W6648423991","https://openalex.org/W6673961057","https://openalex.org/W6675750237","https://openalex.org/W6677759377","https://openalex.org/W6680652380","https://openalex.org/W6980730249"],"related_works":["https://openalex.org/W2089298795","https://openalex.org/W2773002387","https://openalex.org/W1980988957","https://openalex.org/W2766484909","https://openalex.org/W2802800261","https://openalex.org/W1992367803","https://openalex.org/W2163867257","https://openalex.org/W2575757533","https://openalex.org/W2811256493","https://openalex.org/W2898368675"],"abstract_inverted_index":{"Nonnegative":[0],"matrix":[1],"factorization":[2],"(NMF)":[3],"is":[4,32,60,87,110,134,145,161],"a":[5,55,126],"widely":[6],"used":[7],"method":[8],"for":[9,69,136],"blind":[10],"spectral":[11,29],"unmixing":[12],"(SU),":[13],"which":[14,191],"aims":[15],"at":[16],"obtaining":[17],"the":[18,26,35,41,75,81,107,117,122,138,142,149,157,171,176,185,216,219],"endmembers":[19,42,150],"and":[20,48,62,148,151,166,203,209],"corresponding":[21],"fractional":[22],"abundances,":[23],"knowing":[24],"only":[25],"collected":[27,206],"mixing":[28],"data.":[30],"It":[31,115],"noted":[33],"that":[34],"abundance":[36,76,177],"may":[37,43,195],"be":[38,44,196],"sparse":[39,46,49,128],"(i.e.,":[40],"with":[45,67],"distributions)":[47],"NMF":[50,66,129],"tends":[51],"to":[52,54,64,74,169,214],"lead":[53],"unique":[56],"result,":[57],"so":[58],"it":[59,181],"intuitive":[61],"meaningful":[63],"constrain":[65],"sparseness":[68,83,101,173],"solving":[70,137],"SU.":[71],"However,":[72],"due":[73],"sum-to-one":[77],"constraint":[78,91,124],"in":[79,112,178,190],"SU,":[80],"traditional":[82],"measured":[84],"by":[85,207],"L0/L1-norm":[86],"not":[88,183],"an":[89],"effective":[90],"any":[92],"more.":[93],"A":[94],"novel":[95],"measure":[96],"(termed":[97,131],"as":[98,132],"S-measure)":[99],"of":[100,106,175,187,218],"using":[102,121],"higher":[103],"order":[104],"norms":[105],"signal":[108],"vector":[109],"proposed":[111,135,158,220],"this":[113],"paper.":[114],"features":[116],"physical":[118],"significance.":[119],"By":[120],"S-measure":[123],"(SMC),":[125],"gradient-based":[127],"algorithm":[130],"NMF-SMC)":[133],"SU":[139],"problem,":[140],"where":[141],"learning":[143],"rate":[144],"adaptively":[146],"selected,":[147],"abundances":[152],"are":[153,212],"simultaneously":[154],"estimated.":[155],"In":[156],"NMF-SMC,":[159],"there":[160],"no":[162,167],"pure":[163],"index":[164],"assumption":[165],"need":[168],"know":[170],"exact":[172],"degree":[174],"prior.":[179],"Yet,":[180],"does":[182],"require":[184],"preprocessing":[186],"dimension":[188],"reduction":[189],"some":[192],"useful":[193],"information":[194],"lost.":[197],"Experiments":[198],"based":[199],"on":[200],"synthetic":[201],"mixtures":[202],"real-world":[204],"images":[205],"AVIRIS":[208],"HYDICE":[210],"sensors":[211],"performed":[213],"evaluate":[215],"validity":[217],"method.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":17},{"year":2014,"cited_by_count":24},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":16}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
