{"id":"https://openalex.org/W2901664785","doi":"https://doi.org/10.3390/rs10111836","title":"A Noise-Resilient Online Learning Algorithm for Scene Classification","display_name":"A Noise-Resilient Online Learning Algorithm for Scene Classification","publication_year":2018,"publication_date":"2018-11-20","ids":{"openalex":"https://openalex.org/W2901664785","doi":"https://doi.org/10.3390/rs10111836","mag":"2901664785"},"language":"en","primary_location":{"id":"doi:10.3390/rs10111836","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111836","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1836/pdf?version=1542709715","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/10/11/1836/pdf?version=1542709715","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050445079","display_name":"Ling Jian","orcid":"https://orcid.org/0000-0002-9385-5977"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Jian","raw_affiliation_strings":["College of Science, China University of Petroleum, Qingdao 266580, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China University of Petroleum, Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022490692","display_name":"Fuhao Gao","orcid":"https://orcid.org/0009-0003-4650-7800"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuhao Gao","raw_affiliation_strings":["College of Science, China University of Petroleum, Qingdao 266580, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China University of Petroleum, Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767704","display_name":"Peng Ren","orcid":"https://orcid.org/0000-0003-3949-985X"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Ren","raw_affiliation_strings":["College of Information and Control Engineering, China University of Petroleum, Qingdao 266580, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, China University of Petroleum, Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100583281","display_name":"Yunquan Song","orcid":"https://orcid.org/0000-0002-4816-8588"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunquan Song","raw_affiliation_strings":["College of Science, China University of Petroleum, Qingdao 266580, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China University of Petroleum, Qingdao 266580, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046872618","display_name":"Shihua Luo","orcid":"https://orcid.org/0000-0002-0793-7950"},"institutions":[{"id":"https://openalex.org/I59649739","display_name":"Jiangxi University of Finance and Economics","ror":"https://ror.org/03efmyj29","country_code":"CN","type":"education","lineage":["https://openalex.org/I59649739"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shihua Luo","raw_affiliation_strings":["School of Statistics, Jiangxi University of Finance & Economics, Nanchang 330013, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics, Jiangxi University of Finance & Economics, Nanchang 330013, China","institution_ids":["https://openalex.org/I59649739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046872618"],"corresponding_institution_ids":["https://openalex.org/I59649739"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.8616,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89342672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"10","issue":"11","first_page":"1836","last_page":"1836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9918000102043152,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9918000102043152,"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/T12676","display_name":"Machine Learning and ELM","score":0.9894999861717224,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9890999794006348,"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/computer-science","display_name":"Computer science","score":0.8310360908508301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6514763236045837},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5366415977478027},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4978647232055664},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4588584899902344},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.45863425731658936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41351786255836487},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3819761872291565},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30253636837005615},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13596415519714355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8310360908508301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6514763236045837},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5366415977478027},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4978647232055664},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4588584899902344},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.45863425731658936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41351786255836487},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3819761872291565},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30253636837005615},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13596415519714355},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs10111836","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111836","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1836/pdf?version=1542709715","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:aff66fd211fe41479361bbfc9c282b25","is_oa":true,"landing_page_url":"https://doaj.org/article/aff66fd211fe41479361bbfc9c282b25","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 10, Iss 11, p 1836 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/11/1836/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10111836","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 10; Issue 11; Pages: 1836","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10111836","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10111836","pdf_url":"https://www.mdpi.com/2072-4292/10/11/1836/pdf?version=1542709715","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2112453395","display_name":null,"funder_award_id":"61563018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4607532740","display_name":null,"funder_award_id":"61873279 and 61563018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4765083334","display_name":null,"funder_award_id":"618732","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4958374579","display_name":null,"funder_award_id":"Grant No. 2018","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5030790169","display_name":null,"funder_award_id":"16CX02048A","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5167091242","display_name":null,"funder_award_id":"No. 1","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5621071958","display_name":null,"funder_award_id":"2018GSF120020","funder_id":"https://openalex.org/F4320333596","funder_display_name":"Key Technology Research and Development Program of Shandong"},{"id":"https://openalex.org/G5848258319","display_name":null,"funder_award_id":"0 and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G630077093","display_name":null,"funder_award_id":"No. 2018","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8313603624","display_name":null,"funder_award_id":"61873279","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8951484681","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320333596","display_name":"Key Technology Research and Development Program of Shandong","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2901664785.pdf","grobid_xml":"https://content.openalex.org/works/W2901664785.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1560724230","https://openalex.org/W1566135517","https://openalex.org/W1597529531","https://openalex.org/W1605479404","https://openalex.org/W1975588358","https://openalex.org/W1980038761","https://openalex.org/W1989316905","https://openalex.org/W2012592962","https://openalex.org/W2026131661","https://openalex.org/W2030843733","https://openalex.org/W2077723394","https://openalex.org/W2086866337","https://openalex.org/W2089394015","https://openalex.org/W2091280333","https://openalex.org/W2125993116","https://openalex.org/W2127786001","https://openalex.org/W2132087961","https://openalex.org/W2152929147","https://openalex.org/W2157791002","https://openalex.org/W2158054309","https://openalex.org/W2160218441","https://openalex.org/W2162152253","https://openalex.org/W2166765763","https://openalex.org/W2169423212","https://openalex.org/W2179290474","https://openalex.org/W2441489703","https://openalex.org/W2510206144","https://openalex.org/W2515440612","https://openalex.org/W2515866431","https://openalex.org/W2560179108","https://openalex.org/W2565122964","https://openalex.org/W2739802477","https://openalex.org/W2767899548","https://openalex.org/W2774466993","https://openalex.org/W2790332089","https://openalex.org/W2801080335","https://openalex.org/W2806299729","https://openalex.org/W2883982921","https://openalex.org/W2888738034","https://openalex.org/W2889192935","https://openalex.org/W2890732922","https://openalex.org/W3004533406","https://openalex.org/W3009009611","https://openalex.org/W3101781204","https://openalex.org/W3105577662","https://openalex.org/W3106090851","https://openalex.org/W4230765542","https://openalex.org/W4248614128","https://openalex.org/W4285719527","https://openalex.org/W6636033586","https://openalex.org/W6682953061","https://openalex.org/W6683584131","https://openalex.org/W6684549341","https://openalex.org/W6718391320","https://openalex.org/W6746552969","https://openalex.org/W7074671674"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2757182831","https://openalex.org/W2095886385","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W2357523926"],"abstract_inverted_index":{"The":[0],"proliferation":[1],"of":[2,9,43,107,149,167],"remote":[3,102],"sensing":[4,103],"imagery":[5],"motivates":[6],"a":[7,29,90,123],"surge":[8],"research":[10],"interest":[11],"in":[12,105,118,159],"image":[13],"processing":[14],"such":[15],"as":[16,141],"feature":[17],"extraction":[18],"and":[19,56,83,111,131,152,176,191],"scene":[20,25,48],"recognition,":[21],"etc.":[22],"Among":[23],"them,":[24],"recognition":[26,109],"(classification)":[27],"is":[28,129,139,188],"typical":[30],"learning":[31,81,84],"task":[32],"that":[33,181],"focuses":[34],"on":[35,53,173],"exploiting":[36],"annotated":[37],"images":[38],"to":[39,59,89,99,133,144],"infer":[40],"the":[41,74,80,119,146,156,165,182],"category":[42],"an":[44],"unlabeled":[45],"image.":[46],"Existing":[47],"classification":[49,126,186,196],"algorithms":[50],"predominantly":[51],"focus":[52],"static":[54],"data":[55,178],"are":[57,96],"designed":[58],"learn":[60],"discriminant":[61],"information":[62],"from":[63,69,85],"clean":[64],"data.":[65],"They,":[66],"however,":[67],"suffer":[68],"two":[70],"major":[71],"shortcomings,":[72],"i.e.,":[73],"noisy":[75,134,150],"label":[76],"may":[77,87],"negatively":[78],"affect":[79,148],"procedure":[82],"scratch":[86],"lead":[88],"huge":[91],"computational":[92,112],"burden.":[93],"Thus,":[94],"they":[95],"not":[97],"able":[98],"handle":[100],"large-scale":[101],"images,":[104],"terms":[106],"both":[108,174],"accuracy":[110],"cost.":[113],"To":[114],"address":[115],"this":[116],"problem,":[117],"paper,":[120],"we":[121,153],"propose":[122],"noise-resilient":[124,184],"online":[125,185,195],"algorithm,":[127],"which":[128],"scalable":[130],"robust":[132,190],"labels.":[135],"Specifically,":[136],"ramp":[137],"loss":[138,142],"employed":[140],"function":[143,158],"alleviate":[145],"negative":[147],"labels,":[151],"iteratively":[154],"optimize":[155],"decision":[157],"Reproducing":[160],"Kernel":[161],"Hilbert":[162],"Space":[163],"under":[164],"framework":[166],"Online":[168],"Gradient":[169],"Descent":[170],"(OGD).":[171],"Experiments":[172],"synthetic":[175],"real-world":[177],"sets":[179],"demonstrate":[180],"proposed":[183],"algorithm":[187],"more":[189],"sparser":[192],"than":[193],"state-of-the-art":[194],"algorithms.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2018-11-29T00:00:00"}