{"id":"https://openalex.org/W2062649076","doi":"https://doi.org/10.1109/igarss.2014.6947225","title":"Multiple endmember spectral unmixing within a multi-task framework","display_name":"Multiple endmember spectral unmixing within a multi-task framework","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2062649076","doi":"https://doi.org/10.1109/igarss.2014.6947225","mag":"2062649076"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2014.6947225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","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/A5035120678","display_name":"Tatsumi Uezato","orcid":"https://orcid.org/0000-0002-8264-201X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tatsumi Uezato","raw_affiliation_strings":["Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101945184","display_name":"Richard J. Murphy","orcid":"https://orcid.org/0000-0003-3201-4768"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Richard J. Murphy","raw_affiliation_strings":["Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030234520","display_name":"Arman Melkumyan","orcid":"https://orcid.org/0000-0001-9211-4141"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Arman Melkumyan","raw_affiliation_strings":["Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014731691","display_name":"Anna Chlingaryan","orcid":"https://orcid.org/0000-0001-9332-7886"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Anna Chlingaryan","raw_affiliation_strings":["Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102019040","display_name":"Sven Schneider","orcid":"https://orcid.org/0000-0002-1916-5222"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I4210127558","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82","country_code":"AU","type":"facility","lineage":["https://openalex.org/I4210127558"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sven Schneider","raw_affiliation_strings":["Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian Centre for Field Robotics, The University of Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I129604602","https://openalex.org/I4210127558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0271,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73157539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"3454","last_page":"3457"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9706000089645386,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.9967523217201233},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8948286175727844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5405314564704895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5392953157424927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5354008674621582},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.47142356634140015},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45222926139831543},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4446895718574524},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.43456488847732544},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.43355658650398254},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32620251178741455},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07238280773162842}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9967523217201233},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8948286175727844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5405314564704895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5392953157424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5354008674621582},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.47142356634140015},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45222926139831543},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4446895718574524},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.43456488847732544},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.43355658650398254},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32620251178741455},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07238280773162842},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2014.6947225","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947225","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","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":15,"referenced_works":["https://openalex.org/W1974576157","https://openalex.org/W1979286683","https://openalex.org/W1985093013","https://openalex.org/W2119595900","https://openalex.org/W2123519749","https://openalex.org/W2127062304","https://openalex.org/W2136635809","https://openalex.org/W2144881411","https://openalex.org/W2160305377","https://openalex.org/W2166574908","https://openalex.org/W2295820431","https://openalex.org/W4233760599","https://openalex.org/W4299094297","https://openalex.org/W6677658955","https://openalex.org/W6684543871"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W2890371384","https://openalex.org/W2315521504","https://openalex.org/W2563324120","https://openalex.org/W2040756827","https://openalex.org/W2051769241"],"abstract_inverted_index":{"A":[0],"novel":[1],"spectral":[2,12,58,108],"unmixing":[3,28,51],"technique":[4],"is":[5,30,47,110],"presented":[6],"which":[7],"addresses":[8],"the":[9,70,75,120],"problem":[10],"of":[11,126,141],"variability":[13,109],"within":[14,42,61],"each":[15,24,62,145],"endmember":[16,20,63,142],"class":[17,146],"and":[18,67,89,130],"determines":[19],"types":[21],"present":[22],"in":[23,53,113,124],"pixel.":[25],"The":[26,40,116],"proposed":[27],"method":[29],"a":[31,43,138],"multi-task":[32],"framework,":[33],"based":[34],"on":[35],"Multi-task":[36],"Gaussian":[37],"Process":[38],"(MTGP).":[39],"Unmixing":[41],"MTGP":[44],"framework":[45],"(UMTGP)":[46],"different":[48],"to":[49],"conventional":[50,80],"approaches":[52],"that":[54,57,119],"it":[55],"assumes":[56],"variation":[59],"exists":[60],"class.":[64],"Using":[65],"synthetic":[66],"real":[68],"data,":[69],"fractional":[71,128],"abundances":[72],"estimated":[73],"by":[74],"UMTGP":[76,121],"are":[77,102,147],"compared":[78],"with":[79],"methods":[81],"such":[82],"as":[83],"Fully":[84],"Constrained":[85],"Least":[86],"Squares":[87],"(FCLS)":[88],"Multiple":[90],"Endmember":[91],"Spectral":[92],"Mixture":[93],"Analysis":[94],"(MESMA).":[95],"Hyperspectral":[96],"data":[97],"acquired":[98],"from":[99],"field-based":[100],"platforms":[101],"used":[103],"for":[104,144],"evaluation":[105],"because":[106],"intra-class":[107],"commonly":[111],"large":[112],"these":[114],"datasets.":[115],"results":[117],"show":[118],"outperforms":[122],"FCLS":[123],"terms":[125],"estimating":[127],"abundance":[129],"provides":[131],"better":[132],"estimates":[133],"than":[134],"MESMA,":[135],"especially":[136],"when":[137],"small":[139],"number":[140],"spectra":[143],"available.":[148]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}