{"id":"https://openalex.org/W2766731286","doi":"https://doi.org/10.1109/whispers.2014.8077598","title":"End-member extraction using cone non-negativity constraints","display_name":"End-member extraction using cone non-negativity constraints","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2766731286","doi":"https://doi.org/10.1109/whispers.2014.8077598","mag":"2766731286"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2014.8077598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2014.8077598","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5004026628","display_name":"John Gruninger","orcid":null},"institutions":[{"id":"https://openalex.org/I178975111","display_name":"Spectral Sciences (United States)","ror":"https://ror.org/026jgjr74","country_code":"US","type":"company","lineage":["https://openalex.org/I178975111"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Gruninger","raw_affiliation_strings":["Spectral Sciences Inc., Burlington, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Spectral Sciences Inc., Burlington, MA","institution_ids":["https://openalex.org/I178975111"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017677931","display_name":"H. Dothe","orcid":null},"institutions":[{"id":"https://openalex.org/I178975111","display_name":"Spectral Sciences (United States)","ror":"https://ror.org/026jgjr74","country_code":"US","type":"company","lineage":["https://openalex.org/I178975111"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hoang Dothe","raw_affiliation_strings":["Spectral Sciences Inc., Burlington, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Spectral Sciences Inc., Burlington, MA","institution_ids":["https://openalex.org/I178975111"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I178975111"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41176471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"52","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.984499990940094,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7174269556999207},{"id":"https://openalex.org/keywords/cone","display_name":"Cone (formal languages)","score":0.5873274803161621},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5718204975128174},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4954413175582886},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4866812825202942},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4821300506591797},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.44750627875328064},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4246172606945038},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42179277539253235},{"id":"https://openalex.org/keywords/linear-inequality","display_name":"Linear inequality","score":0.414836585521698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3855036497116089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3763432800769806},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3693213164806366},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1255529820919037},{"id":"https://openalex.org/keywords/inequality","display_name":"Inequality","score":0.12135905027389526},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.09445685148239136}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7174269556999207},{"id":"https://openalex.org/C30014739","wikidata":"https://www.wikidata.org/wiki/Q5159445","display_name":"Cone (formal languages)","level":2,"score":0.5873274803161621},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5718204975128174},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4954413175582886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4866812825202942},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4821300506591797},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.44750627875328064},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4246172606945038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42179277539253235},{"id":"https://openalex.org/C84135550","wikidata":"https://www.wikidata.org/wiki/Q3154022","display_name":"Linear inequality","level":3,"score":0.414836585521698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3855036497116089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3763432800769806},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3693213164806366},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1255529820919037},{"id":"https://openalex.org/C45555294","wikidata":"https://www.wikidata.org/wiki/Q28113351","display_name":"Inequality","level":2,"score":0.12135905027389526},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.09445685148239136},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2014.8077598","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2014.8077598","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5600000023841858,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1524090374","https://openalex.org/W1983939131","https://openalex.org/W1988445439","https://openalex.org/W2070424424","https://openalex.org/W2119886624","https://openalex.org/W2150673362","https://openalex.org/W2152557171","https://openalex.org/W2165755981","https://openalex.org/W2952779762","https://openalex.org/W6646529452"],"related_works":["https://openalex.org/W2351387116","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2361100278","https://openalex.org/W2792706544","https://openalex.org/W1658347130","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2398836525"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,19,71],"new":[4],"factorization":[5],"approach":[6,91],"for":[7],"hyperspectral":[8],"data":[9,29,61],"based":[10,83],"on":[11,84],"non-negativity":[12],"constraints.":[13,77],"The":[14,63,78,90],"method":[15],"does":[16],"not":[17],"assume":[18],"one":[20,22],"to":[21,49,97],"correspondence":[23],"between":[24],"the":[25,28,32,42,50,56,60,85,103],"pseudo-rank":[26],"of":[27,34,44,52,55,73,80,87,102],"matrix":[30],"and":[31,70],"number":[33,43,51],"unique":[35,45],"components":[36,46],"present.":[37],"Rather":[38],"it":[39],"assumes":[40],"that":[41],"is":[47,65,82,92],"related":[48],"extreme":[53],"points":[54],"cone":[57,64],"formed":[58],"by":[59,67],"matrix.":[62],"represented":[66],"singular":[68],"vectors":[69],"set":[72],"linear":[74],"homogeneous":[75],"inequality":[76],"extraction":[79],"extremes":[81],"identification":[86],"non-redundant":[88],"inequalities.":[89],"illustrated":[93],"in":[94],"an":[95,98],"application":[96],"AVIRIS":[99],"spectral":[100],"image":[101],"Cuprite":[104],"mining":[105],"site.":[106]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}