{"id":"https://openalex.org/W2119159722","doi":"https://doi.org/10.1109/igarss.2011.6050032","title":"Domain separation for efficient adaptive active learning","display_name":"Domain separation for efficient adaptive active learning","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2119159722","doi":"https://doi.org/10.1109/igarss.2011.6050032","mag":"2119159722"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2011.6050032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6050032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.wur.nl/en/publications/domain-separation-for-efficient-adaptive-active-learning","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084561935","display_name":"Giona Matasci","orcid":null},"institutions":[{"id":"https://openalex.org/I97565354","display_name":"University of Lausanne","ror":"https://ror.org/019whta54","country_code":"CH","type":"education","lineage":["https://openalex.org/I97565354"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Giona Matasci","raw_affiliation_strings":["Institute of Geomatics and Analysis of Risk, University of Lausanne, Lausanne, Switzerland","Institute of Geomatics and Analysis of Risk, University of Lausanne, Switzerland#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Geomatics and Analysis of Risk, University of Lausanne, Lausanne, Switzerland","institution_ids":["https://openalex.org/I97565354"]},{"raw_affiliation_string":"Institute of Geomatics and Analysis of Risk, University of Lausanne, Switzerland#TAB#","institution_ids":["https://openalex.org/I97565354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005192117","display_name":"Devis Tuia","orcid":"https://orcid.org/0000-0003-0374-2459"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Devis Tuia","raw_affiliation_strings":["Image Processing Laboratory (IPL), Niversitat de Val\u00e8ncia, Valencia, Spain","Image Processing Laboratory (IPL). Universitat de Val\u00e8ncia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), Niversitat de Val\u00e8ncia, Valencia, Spain","institution_ids":[]},{"raw_affiliation_string":"Image Processing Laboratory (IPL). Universitat de Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068472081","display_name":"Mikha\u00efl Kanevski","orcid":"https://orcid.org/0000-0001-6602-6551"},"institutions":[{"id":"https://openalex.org/I97565354","display_name":"University of Lausanne","ror":"https://ror.org/019whta54","country_code":"CH","type":"education","lineage":["https://openalex.org/I97565354"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Mikhail Kanevski","raw_affiliation_strings":["Institute of Geomatics and Analysis of Risk, University of Lausanne, Lausanne, Switzerland","Institute of Geomatics and Analysis of Risk, University of Lausanne, Switzerland#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Geomatics and Analysis of Risk, University of Lausanne, Lausanne, Switzerland","institution_ids":["https://openalex.org/I97565354"]},{"raw_affiliation_string":"Institute of Geomatics and Analysis of Risk, University of Lausanne, Switzerland#TAB#","institution_ids":["https://openalex.org/I97565354"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3189,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84756801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"3716","last_page":"3719"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9968000054359436,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7620012760162354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7592765092849731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7494133114814758},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7263950705528259},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5838594436645508},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5777354836463928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5398051738739014},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5234660506248474},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4942200481891632},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4667520821094513},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46305108070373535},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4118247330188751},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17484408617019653}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7620012760162354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7592765092849731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7494133114814758},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7263950705528259},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5838594436645508},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5777354836463928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5398051738739014},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5234660506248474},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4942200481891632},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4667520821094513},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46305108070373535},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4118247330188751},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17484408617019653},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/igarss.2011.6050032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6050032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:library.wur.nl:wurpubs/566217","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/domain-separation-for-efficient-adaptive-active-learning","pdf_url":null,"source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"ISBN: 9781457710056","raw_type":"Article in monograph or in proceedings"},{"id":"pmh:oai:iris.unil.ch:iris/57990","is_oa":true,"landing_page_url":"https://iris.unil.ch/handle/iris/57990","pdf_url":"https://iris.unil.ch/bitstreams/05476acb-c0e6-4120-8d3c-e35e68205d63/download","source":{"id":"https://openalex.org/S7407055444","display_name":"IRIS","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"pmh:oai:serval.unil.ch:BIB_166A39C0057E","is_oa":true,"landing_page_url":"https://serval.unil.ch/notice/serval:BIB_166A39C0057E","pdf_url":null,"source":{"id":"https://openalex.org/S4306401797","display_name":"SERVAL (Universit\u00e9 de Lausanne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210093590","host_organization_name":"Swiss School of Archaeology in Greece","host_organization_lineage":["https://openalex.org/I4210093590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc. IEEE IGARSS 2011, Vancouver, Canada","raw_type":"info:eu-repo/semantics/submittedVersion"}],"best_oa_location":{"id":"pmh:oai:library.wur.nl:wurpubs/566217","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/domain-separation-for-efficient-adaptive-active-learning","pdf_url":null,"source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"ISBN: 9781457710056","raw_type":"Article in monograph or in proceedings"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W77777798","https://openalex.org/W1664950380","https://openalex.org/W2100835628","https://openalex.org/W2107131609","https://openalex.org/W2114154403","https://openalex.org/W2122838776","https://openalex.org/W2125201264","https://openalex.org/W2125458569","https://openalex.org/W2137900926","https://openalex.org/W2149681371","https://openalex.org/W2153635508","https://openalex.org/W2154772499","https://openalex.org/W2165698076","https://openalex.org/W2168876499","https://openalex.org/W3120421331","https://openalex.org/W4250800088","https://openalex.org/W6603082663","https://openalex.org/W6637241018","https://openalex.org/W6675303745"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W4287263085","https://openalex.org/W3186065094","https://openalex.org/W3204418343","https://openalex.org/W3093803318","https://openalex.org/W3132602785","https://openalex.org/W4390401377"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,9,13,17,34,53,73,92,138],"procedure":[4],"aimed":[5],"at":[6],"efficiently":[7],"adapting":[8],"classifier":[10,93],"trained":[11],"on":[12,101,137],"source":[14],"image":[15,62],"to":[16,69,108,129,155],"similar":[18],"target":[19,31,61,103,134],"image.":[20,104],"The":[21],"adaptation":[22],"is":[23],"carried":[24],"out":[25],"through":[26],"active":[27,97],"queries":[28,98],"in":[29,72],"the":[30,39,47,60,76,83,102,106,109,113,116,120,147,150],"domain":[32,88],"following":[33],"strategy":[35],"particularly":[36],"designed":[37],"for":[38],"case":[40],"where":[41],"class":[42],"distributions":[43],"have":[44],"shifted":[45],"between":[46],"two":[48],"images.":[49],"We":[50],"first":[51],"suggest":[52],"pre-selection":[54],"of":[55,75,112,140,143,149],"candidate":[56],"pixels":[57,122],"issued":[58],"from":[59],"by":[63,82],"keeping":[64],"only":[65],"those":[66],"samples":[67,114],"appearing":[68],"be":[70],"lying":[71],"region":[74],"input":[77],"space":[78],"not":[79],"yet":[80],"covered":[81],"existing":[84,156],"ground":[85],"truth":[86],"(source":[87,132],"pixels).":[89],"Then,":[90],"exploiting":[91],"integrating":[94],"instance":[95],"weights,":[96],"are":[99,123],"performed":[100],"As":[105],"inclusion":[107],"training":[110,121],"set":[111],"progresses,":[115],"weights":[117],"associated":[118],"with":[119],"updated":[124],"using":[125],"different":[126],"criteria":[127],"according":[128],"their":[130],"origin":[131],"or":[133],"domain).":[135],"Experiments":[136],"pair":[139],"QuickBird":[141],"images":[142],"urban":[144],"scenes":[145],"prove":[146],"validity":[148],"proposed":[151],"approach":[152],"if":[153],"compared":[154],"benchmark":[157],"methods.":[158]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}