{"id":"https://openalex.org/W2586352524","doi":"https://doi.org/10.1109/smc.2016.7844378","title":"Local one-dimensional embedding interpolation for hyperspectral image classification","display_name":"Local one-dimensional embedding interpolation for hyperspectral image classification","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2586352524","doi":"https://doi.org/10.1109/smc.2016.7844378","mag":"2586352524"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2016.7844378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844378","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"article","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/A5009805944","display_name":"Yalong Song","orcid":"https://orcid.org/0000-0002-7996-8318"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalong Song","raw_affiliation_strings":["School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339334","display_name":"Hong Li","orcid":"https://orcid.org/0000-0001-5597-5479"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Li","raw_affiliation_strings":["School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101510401","display_name":"Huizhen Li","orcid":"https://orcid.org/0000-0002-2398-5565"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huizhen Li","raw_affiliation_strings":["School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of mathematics and statistics, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026977092","display_name":"Yantao Wei","orcid":"https://orcid.org/0000-0001-7225-1958"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yantao Wei","raw_affiliation_strings":["School of Educational Information Technology, Central China Normal University, Wuhan, China","School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Educational Information Technology, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]},{"raw_affiliation_string":"School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23657303,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2016","issue":null,"first_page":"001034","last_page":"001039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.89006507396698},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6728997230529785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5847578048706055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5834172964096069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5804684162139893},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5608312487602234},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5606762170791626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5586978197097778},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4754892587661743},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4541151523590088},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.351593017578125},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08029276132583618}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.89006507396698},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6728997230529785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5847578048706055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5834172964096069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5804684162139893},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5608312487602234},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5606762170791626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5586978197097778},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4754892587661743},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4541151523590088},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.351593017578125},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08029276132583618},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/smc.2016.7844378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2016.7844378","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"mag:2743626289","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/201702228831167657","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W626292722","https://openalex.org/W1937669826","https://openalex.org/W1972499291","https://openalex.org/W1972524915","https://openalex.org/W1979730959","https://openalex.org/W1997565609","https://openalex.org/W2001298023","https://openalex.org/W2004746362","https://openalex.org/W2008847349","https://openalex.org/W2016860790","https://openalex.org/W2044184146","https://openalex.org/W2056621966","https://openalex.org/W2087263574","https://openalex.org/W2094304765","https://openalex.org/W2132467081","https://openalex.org/W2136251662","https://openalex.org/W2153747028","https://openalex.org/W2164330327","https://openalex.org/W2235571288","https://openalex.org/W2236497445","https://openalex.org/W2237758977","https://openalex.org/W2250547309","https://openalex.org/W2417947228","https://openalex.org/W4242361212","https://openalex.org/W4298726855","https://openalex.org/W6717226324"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2072166414","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W4382618745","https://openalex.org/W1973775000"],"abstract_inverted_index":{"In":[0,21,73,131],"the":[1,16,44,46,55,58,70,82,98,107,116,133,144,152,162,166,171,179,188,198,205,208],"hyperspectral":[2,36,201],"image":[3,37],"classification":[4,19,38,186],"area,":[5],"a":[6,13,78],"few":[7],"number":[8],"of":[9,18,48,60,118,147,159,178,207],"labeled":[10,71,99,122,140,148,163],"samples":[11,63,100,123,141],"is":[12,64],"bottleneck":[14],"for":[15,35],"improvement":[17],"accuracy.":[20],"order":[22],"to":[23,128],"tackle":[24],"this":[25,74],"problem,":[26],"multiple":[27,89],"one-dimensional":[28,91,108],"embedding":[29,92],"interpolation":[30,93],"(M1DEI)":[31],"has":[32],"been":[33],"used":[34,200],"and":[39,101,124,174],"achieved":[40],"promising":[41,193],"results.":[42,194],"Despite":[43],"success,":[45],"complexity":[47,117],"M1DEI":[49,83],"prevents":[50],"its":[51],"practical":[52],"application.":[53],"On":[54],"other":[56,184],"hand,":[57],"percentage":[59],"newly":[61,139],"added":[62],"set":[65,203],"by":[66,80],"experience":[67],"when":[68],"enlarging":[69],"set.":[72],"paper":[75],"we":[76,155],"develop":[77],"method":[79,84,191],"extending":[81],"with":[85,161,183],"local":[86,90,103,112,134],"strategy,":[87],"called":[88],"(ML1DEI).":[94],"We":[95],"only":[96,121],"map":[97],"their":[102,125],"spatial":[104,145,172],"neighbors":[105,126],"into":[106],"(1D)":[109],"space.":[110],"The":[111],"strategy":[113,135],"can":[114,156,169],"reduce":[115],"M1DEI,":[119],"since":[120],"need":[127],"be":[129],"mapped.":[130],"addition,":[132],"ensures":[136],"all":[137,158],"these":[138],"come":[142],"from":[143],"neighborhood":[146],"samples.":[149,164,181],"Then,":[150],"during":[151],"merging":[153],"stage,":[154],"incorporate":[157,170],"them":[160],"Moreover,":[165],"proposed":[167,189,209],"ML1DEI":[168,190],"information":[173],"make":[175],"full":[176],"use":[177],"unlabeled":[180],"Compared":[182],"spatial-spectral":[185],"methods,":[187],"obtains":[192],"Experimental":[195],"results":[196],"on":[197],"commonly":[199],"data":[202],"validate":[204],"effectiveness":[206],"method.":[210]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
