{"id":"https://openalex.org/W2907511776","doi":"https://doi.org/10.1109/jstars.2018.2886821","title":"An Online Multiview Learning Algorithm for PolSAR Data Real-Time Classification","display_name":"An Online Multiview Learning Algorithm for PolSAR Data Real-Time Classification","publication_year":2018,"publication_date":"2018-12-25","ids":{"openalex":"https://openalex.org/W2907511776","doi":"https://doi.org/10.1109/jstars.2018.2886821","mag":"2907511776"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2886821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2886821","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5049695170","display_name":"Xiangli Nie","orcid":"https://orcid.org/0000-0001-5208-4670"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangli Nie","raw_affiliation_strings":["State Key Lab of Management and Control for Complex System, Institute of Automation, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5208-4670","affiliations":[{"raw_affiliation_string":"State Key Lab of Management and Control for Complex System, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021998285","display_name":"Shuguang Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuguang Ding","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011743488","display_name":"Xiayuan Huang","orcid":"https://orcid.org/0000-0002-3325-933X"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiayuan Huang","raw_affiliation_strings":["State Key Lab of Management and Control for Complex System, Institute of Automation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of Management and Control for Complex System, Institute of Automation, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026688050","display_name":"Hong Qiao","orcid":"https://orcid.org/0000-0001-6384-3687"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Qiao","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6384-3687","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100335192","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0001-7355-0941"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7355-0941","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067046312","display_name":"Zhong\u2010Ping Jiang","orcid":"https://orcid.org/0000-0002-4868-9359"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhong-Ping Jiang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-4868-9359","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":14.4193,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.98303678,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":"1","first_page":"302","last_page":"320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9495999813079834,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9440000057220459,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/computer-science","display_name":"Computer science","score":0.8153355717658997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6335298418998718},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5545229911804199},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.51845782995224},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.45963746309280396},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4448779821395874},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4417732059955597},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.43647637963294983},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4259202480316162},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4196022152900696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41471272706985474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40874823927879333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3878938853740692},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32283511757850647},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20960140228271484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8153355717658997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6335298418998718},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5545229911804199},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.51845782995224},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.45963746309280396},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4448779821395874},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4417732059955597},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.43647637963294983},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4259202480316162},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4196022152900696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41471272706985474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40874823927879333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3878938853740692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32283511757850647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20960140228271484},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2018.2886821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2886821","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G2012007305","display_name":null,"funder_award_id":"U1435220","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4681919330","display_name":null,"funder_award_id":"61602483","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6130823433","display_name":null,"funder_award_id":"91648205","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7501480075","display_name":null,"funder_award_id":"61802408","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8361417385","display_name":null,"funder_award_id":"4174107","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W129087361","https://openalex.org/W1421632428","https://openalex.org/W1670132599","https://openalex.org/W1981539283","https://openalex.org/W1985194020","https://openalex.org/W1988790447","https://openalex.org/W2001337397","https://openalex.org/W2008826820","https://openalex.org/W2018775529","https://openalex.org/W2040870580","https://openalex.org/W2048578702","https://openalex.org/W2048679005","https://openalex.org/W2052190325","https://openalex.org/W2053184029","https://openalex.org/W2054291723","https://openalex.org/W2057571734","https://openalex.org/W2059644815","https://openalex.org/W2074866567","https://openalex.org/W2077723394","https://openalex.org/W2086016807","https://openalex.org/W2091823356","https://openalex.org/W2104554891","https://openalex.org/W2109743529","https://openalex.org/W2119393863","https://openalex.org/W2148825261","https://openalex.org/W2150388078","https://openalex.org/W2150621701","https://openalex.org/W2153635508","https://openalex.org/W2160218441","https://openalex.org/W2186500555","https://openalex.org/W2240204456","https://openalex.org/W2248623186","https://openalex.org/W2288628559","https://openalex.org/W2306802236","https://openalex.org/W2329184523","https://openalex.org/W2408432900","https://openalex.org/W2516919730","https://openalex.org/W2556793696","https://openalex.org/W2576338689","https://openalex.org/W2751733204","https://openalex.org/W2754361766","https://openalex.org/W2754863596","https://openalex.org/W2761412452","https://openalex.org/W2792151357","https://openalex.org/W3009009611","https://openalex.org/W4292022450","https://openalex.org/W6636883489","https://openalex.org/W6675682377","https://openalex.org/W6677803693","https://openalex.org/W6681723013","https://openalex.org/W6683584131","https://openalex.org/W6714150371"],"related_works":["https://openalex.org/W4210966920","https://openalex.org/W2156233651","https://openalex.org/W1975547468","https://openalex.org/W2804627982","https://openalex.org/W2001679188","https://openalex.org/W4205493345","https://openalex.org/W2016342027","https://openalex.org/W2196068029","https://openalex.org/W2310826128","https://openalex.org/W2974328778"],"abstract_inverted_index":{"Polarimetric":[0],"synthetic":[1],"aperture":[2],"radar":[3],"(PolSAR)":[4],"data":[5,80],"are":[6,89,151],"sequentially":[7],"acquired":[8],"and":[9,14,58,86,95,110,130,137,147,153,191,211,215,234],"usually":[10],"large":[11],"scale.":[12],"Fast":[13],"accurate":[15],"classification":[16,33,149],"is":[17,42,180],"particularly":[18],"important":[19],"for":[20,46,53,61,78,144,187],"their":[21],"applications.":[22],"By":[23],"introducing":[24],"online":[25,232],"learning,":[26],"the":[27,108,124,132,138,154,168,174,220,225,229],"PolSAR":[28,79,93,185],"system":[29],"can":[30],"learn":[31],"a":[32,37,54,118,165,203],"model":[34,121],"incrementally":[35],"from":[36],"stream":[38],"of":[39,43,98,113,126,170,173,228],"instances,":[40],"which":[41],"high":[44],"efficiency":[45],"newly":[47],"arrived":[48],"samples":[49],"processing,":[50],"strong":[51],"adaptability":[52],"dynamically":[55],"changing":[56],"environment,":[57],"excellent":[59],"scalability":[60],"rapidly":[62],"increasing":[63],"data.":[64],"In":[65,104,160],"this":[66],"paper,":[67],"we":[68,116,162],"propose":[69],"an":[70],"Online":[71],"Multi-view":[72],"Passive-Aggressive":[73],"learning":[74,236],"algorithm,":[75],"named":[76],"OMPA,":[77],"real-time":[81],"classification.":[82],"The":[83,141,176],"polarimetric,":[84],"color,":[85],"texture":[87],"features":[88,99],"extracted":[90],"to":[91,101,106],"characterize":[92],"data,":[94],"each":[96,135],"type":[97],"corresponds":[100],"one":[102],"view.":[103],"order":[105],"exploit":[107],"consistency":[109],"complementary":[111],"property":[112],"these":[114],"views,":[115],"give":[117],"new":[119],"optimization":[120],"that":[122,199],"ensembles":[123],"classifiers":[125],"multiple":[127],"distinct":[128],"views":[129],"enforces":[131],"agreement":[133],"between":[134],"predictor":[136],"combined":[139],"predictor.":[140],"corresponding":[142],"algorithms":[143],"both":[145],"binary":[146],"multiclass":[148],"tasks":[150],"derived,":[152],"update":[155],"steps":[156],"have":[157],"analytical":[158],"solutions.":[159],"addition,":[161],"rigorously":[163],"derive":[164],"bound":[166],"on":[167,182,219],"number":[169],"prediction":[171],"mistakes":[172],"method.":[175],"proposed":[177],"OMPA":[178,200],"algorithm":[179],"evaluated":[181],"two":[183],"real":[184],"datasets":[186],"built-up":[188],"areas":[189],"extraction":[190],"land":[192],"cover":[193],"classification,":[194],"respectively.":[195],"Experimental":[196],"results":[197,227],"demonstrate":[198],"consistently":[201],"maintains":[202],"smaller":[204],"mistake":[205],"rate":[206],"with":[207,224],"low":[208],"time":[209],"cost":[210],"achieves":[212],"about":[213],"1%":[214],"2%":[216],"accuracy":[217],"improvements":[218],"datasets,":[221],"respectively,":[222],"compared":[223],"best":[226],"previously":[230],"known":[231],"single-view":[233],"multiview":[235],"methods.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}