{"id":"https://openalex.org/W2954929510","doi":"https://doi.org/10.1109/whispers.2018.8747247","title":"Parameter Estimation For Blind l<sub>q</sub> Hyperspectral Unmixing Using Bayesian Optimization","display_name":"Parameter Estimation For Blind l<sub>q</sub> Hyperspectral Unmixing Using Bayesian Optimization","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2954929510","doi":"https://doi.org/10.1109/whispers.2018.8747247","mag":"2954929510"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2018.8747247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th 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/A5079644472","display_name":"Jakob Sigur\u00f0sson","orcid":"https://orcid.org/0000-0002-4978-9722"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jakob Sigurdsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069292094","display_name":"Magn\u00fas \u00d6. \u00dalfarsson","orcid":"https://orcid.org/0000-0002-0461-040X"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Magnus O. Ulfarsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008277487","display_name":"J\u00f3hannes R. Sveinsson","orcid":"https://orcid.org/0000-0001-6309-3126"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Johannes R. Sveinsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165368041"],"apc_list":null,"apc_paid":null,"fwci":1.1619,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.80606454,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"12","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.994700014591217,"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":0.9793633222579956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5827878713607788},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5812940001487732},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5744432806968689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5419564843177795},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.48269057273864746},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.44191643595695496},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4146050810813904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29276907444000244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24222332239151}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9793633222579956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5827878713607788},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5812940001487732},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5744432806968689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5419564843177795},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.48269057273864746},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.44191643595695496},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4146050810813904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29276907444000244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24222332239151},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2018.8747247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2018.8747247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1902027874","https://openalex.org/W1966661320","https://openalex.org/W1974448798","https://openalex.org/W2005818237","https://openalex.org/W2032944446","https://openalex.org/W2101837437","https://openalex.org/W2103559027","https://openalex.org/W2117561707","https://openalex.org/W2131241448","https://openalex.org/W2163886442","https://openalex.org/W2295820431","https://openalex.org/W2506064001","https://openalex.org/W2738563291","https://openalex.org/W2774517539","https://openalex.org/W2964172739","https://openalex.org/W3122463936","https://openalex.org/W4233760599","https://openalex.org/W6677764299","https://openalex.org/W6678911119","https://openalex.org/W6746968042"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W3034864990","https://openalex.org/W4230131218"],"abstract_inverted_index":{"Blind":[0],"hyperspectral":[1,18,23,65,85],"unmixing":[2,24,100],"is":[3,26,37],"the":[4,9,15,45,48,73,92,99],"task":[5],"of":[6,22,47,94],"estimating":[7,34],"both":[8],"pure":[10],"material":[11],"spectra":[12],"(endmembers),":[13],"and":[14,40],"abundances":[16],"in":[17],"images.":[19],"The":[20],"performance":[21],"methods":[25],"very":[27],"often":[28],"dependent":[29],"on":[30],"tuning":[31,61,82,95],"parameters.":[32],"Accurately":[33],"these":[35],"parameters":[36,62,83,96],"computationally":[38],"intensive":[39],"this":[41,52],"can":[42,76,97],"severely":[43],"limit":[44],"complexity":[46],"underlying":[49],"model.":[50],"In":[51],"paper,":[53],"we":[54,70,88],"propose":[55],"using":[56],"Bayesian":[57],"optimization":[58],"to":[59,80],"estimate":[60,81],"for":[63,84],"blind":[64],"unmixing.":[66,86],"Using":[67],"real":[68],"data,":[69],"show":[71,89],"that":[72,90],"proposed":[74],"method":[75],"be":[77],"successfully":[78],"applied":[79],"Also,":[87],"increasing":[91],"number":[93],"improve":[98],"results.":[101]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}