{"id":"https://openalex.org/W3207570343","doi":"https://doi.org/10.1109/igarss47720.2021.9553498","title":"An Approach Based on Low Resolution Land-Cover-Maps and Domain Adaptation to Define Representative Training Sets at Large Scale","display_name":"An Approach Based on Low Resolution Land-Cover-Maps and Domain Adaptation to Define Representative Training Sets at Large Scale","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3207570343","doi":"https://doi.org/10.1109/igarss47720.2021.9553498","mag":"3207570343"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","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/A5069989321","display_name":"Iwona Podsiadlo","orcid":"https://orcid.org/0000-0003-0178-5316"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Iwona Podsiadlo","raw_affiliation_strings":["University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008344573","display_name":"Claudia Paris","orcid":"https://orcid.org/0000-0002-7189-6268"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudia Paris","raw_affiliation_strings":["University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["University of Trento, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069989321"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":0.2517,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59973769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"32","issue":null,"first_page":"313","last_page":"316"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9922000169754028,"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":0.9922000169754028,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.977400004863739,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9728000164031982,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6670407056808472},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5956723690032959},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5904148817062378},{"id":"https://openalex.org/keywords/thematic-map","display_name":"Thematic map","score":0.5549818873405457},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5483090877532959},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.532250165939331},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.5314696431159973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46070992946624756},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43860530853271484},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3496834635734558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18834349513053894},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.18130749464035034},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.1263982653617859},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12122842669487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6670407056808472},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5956723690032959},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5904148817062378},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.5549818873405457},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5483090877532959},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.532250165939331},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.5314696431159973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46070992946624756},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43860530853271484},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3496834635734558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18834349513053894},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.18130749464035034},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.1263982653617859},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12122842669487},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/364407","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/document/9553498","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320318240","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1500583457","https://openalex.org/W2149466042","https://openalex.org/W2159570078","https://openalex.org/W2166736950","https://openalex.org/W2598998899","https://openalex.org/W2766742564","https://openalex.org/W2808097118","https://openalex.org/W2945987083","https://openalex.org/W2990709181","https://openalex.org/W3006592188","https://openalex.org/W3154664134","https://openalex.org/W4288076010","https://openalex.org/W6770884442"],"related_works":["https://openalex.org/W2365305234","https://openalex.org/W2546748626","https://openalex.org/W2132503437","https://openalex.org/W2786391746","https://openalex.org/W4381430104","https://openalex.org/W2995102745","https://openalex.org/W4226059458","https://openalex.org/W2914559142","https://openalex.org/W1990237101","https://openalex.org/W3196471634"],"abstract_inverted_index":{"The":[0,140,162],"accurate":[1],"classification":[2],"of":[3,17,21,51,87,159,171],"remote":[4],"sensing":[5],"(RS)":[6],"data":[7,19,61,97,110],"at":[8],"large":[9],"scale":[10],"is":[11,68,101],"typically":[12],"hampered":[13],"by":[14],"the":[15,22,47,52,65,84,88,109,121,131,146,157,160,178],"availability":[16],"training":[18,39,66,99,122,164,180],"representative":[20],"whole":[23],"study":[24],"area.":[25],"To":[26],"solve":[27],"this":[28],"problem,":[29],"we":[30],"propose":[31],"a":[32,105],"method":[33],"that":[34],"aims":[35],"to":[36,70,103,119,174],"enlarge":[37,120],"existing":[38],"sets":[40],"leveraging":[41],"publicly":[42],"available":[43,48],"thematic":[44,49],"products.":[45],"First,":[46],"product":[50],"target":[53,74,78],"domain":[54,90],"(":[55,91],"<tex":[56,92,132],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[57,93,133],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$D_{T}$</tex>":[58,134],")":[59,95],"(RS":[60,96],"geographically":[62],"distant":[63],"from":[64,130],"samples)":[67],"processed":[69],"extract":[71],"few":[72],"labeled":[73,77],"samples.":[75],"These":[76],"samples":[79,86,129],"are":[80,111,135],"jointly":[81],"used":[82],"with":[83,177],"annotated":[85,128],"source":[89],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$D_{S}$</tex>":[94],"where":[98,108],"set":[100,123,165],"available)":[102],"find":[104],"mapping":[106],"space":[107,116],"aligned.":[112],"This":[113],"common":[114],"latent":[115],"allows":[117],"us":[118],"in":[124,143],"an":[125,167],"unsupervised":[126],"(no":[127],"required)":[136],"but":[137],"reliable":[138],"way.":[139],"results":[141],"obtained":[142,176],"Amazon":[144],"using":[145],"Copernicus":[147],"Global":[148],"Land":[149,152],"Service":[150],"-":[151],"cover":[153],"(CGLS-LC)":[154],"map":[155],"demonstrate":[156],"effectiveness":[158],"method.":[161],"enlarged":[163],"achieves":[166],"Overall":[168],"Accuracy":[169],"(OA)":[170],"87%":[172],"compared":[173],"80%":[175],"initial":[179],"set.":[181]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2021-10-25T00:00:00"}
