{"id":"https://openalex.org/W4402260754","doi":"https://doi.org/10.1109/igarss53475.2024.10642610","title":"Data on Demand: Automatic Generation of Customized Datasets for the Training of Building Detection in Remote Sensing Imagery","display_name":"Data on Demand: Automatic Generation of Customized Datasets for the Training of Building Detection in Remote Sensing Imagery","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402260754","doi":"https://doi.org/10.1109/igarss53475.2024.10642610"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10642610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101994555","display_name":"Hai Huang","orcid":"https://orcid.org/0000-0001-8745-8142"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai Huang","raw_affiliation_strings":["Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108332486","display_name":"Kevin Hild","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kevin Hild","raw_affiliation_strings":["Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100408478","display_name":"Yixuan Wang","orcid":"https://orcid.org/0000-0003-3079-5572"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yixuan Wang","raw_affiliation_strings":["Technical University of Munich,Professorship Land Surface-Atmosphere Interactions,Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Professorship Land Surface-Atmosphere Interactions,Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079258186","display_name":"Marco K\u00f6rner","orcid":"https://orcid.org/0000-0002-9186-4175"},"institutions":[{"id":"https://openalex.org/I4210111978","display_name":"Remote Sensing Solutions (Germany)","ror":"https://ror.org/023cs4y60","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210111978"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marco K\u00f6rner","raw_affiliation_strings":["Technical University of Munich,Chair of Remote Sensing Technology,Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Chair of Remote Sensing Technology,Munich,Germany","institution_ids":["https://openalex.org/I4210111978","https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051753781","display_name":"Helmut Mayer","orcid":"https://orcid.org/0000-0002-9439-2695"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Helmut Mayer","raw_affiliation_strings":["Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universität der Bundeswehr München,Institute for Applied Computer Science,Neubiberg,Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5934,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.84395173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"254","last_page":"257"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9959999918937683,"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":0.9959999918937683,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/computer-science","display_name":"Computer science","score":0.7125536203384399},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6722127199172974},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4768601357936859},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4419352412223816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37947943806648254},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10046112537384033},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05853384733200073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125536203384399},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6722127199172974},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4768601357936859},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4419352412223816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37947943806648254},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10046112537384033},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05853384733200073},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss53475.2024.10642610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:mediatum.ub.tum.de:node/1778938","is_oa":false,"landing_page_url":"https://mediatum.ub.tum.de/1778938","pdf_url":null,"source":{"id":"https://openalex.org/S4306400453","display_name":"mediaTUM \u2013 the media and publications repository of the Technical University Munich (Technical University Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"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":"ConferencePaper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2559545830","https://openalex.org/W2609402060","https://openalex.org/W2751236261","https://openalex.org/W2811199523","https://openalex.org/W3016947168","https://openalex.org/W4292793893","https://openalex.org/W4387829113"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659","https://openalex.org/W4394050964","https://openalex.org/W2551249631"],"abstract_inverted_index":{"In":[0,49],"the":[1,97,101,109,120,124,139,145,152,176,183,186],"era":[2],"of":[3,34,46,59,123,147,154,185],"deep":[4],"learning,":[5],"training":[6],"data":[7,39,62,121,181],"play":[8],"an":[9,54,129],"essential":[10],"role.":[11],"Yet,":[12],"their":[13],"generation":[14,58,102],"is":[15,158],"expensive":[16],"concerning":[17,143],"both":[18,144],"cost":[19],"and":[20,41,65],"time.":[21],"Besides":[22],"this,":[23],"it":[24],"often":[25],"suffers":[26],"from":[27,67,96],"(1)":[28],"insufficient":[29],"data,":[30],"(2)":[31],"fixed":[32],"definition":[33],"categories":[35],"possibly":[36],"leading":[37],"to":[38,73,107,111,119,138],"imbalance,":[40],"(3)":[42],"difficult":[43],"quality":[44],"control":[45],"manual":[47,165],"annotations.":[48],"this":[50,157],"paper,":[51],"we":[52],"propose":[53],"approach":[55],"for":[56,63,87,169],"automatic":[57,94],"urban":[60],"building":[61],"detection":[64],"classification":[66],"remote":[68],"sensing":[69],"imagery":[70],"which":[71,82],"attempts":[72],"deal":[74],"with":[75,172,178],"these":[76],"issues.":[77],"Datasets":[78],"in":[79,91,160],"popular":[80],"format,":[81],"can":[83,104,133],"be":[84,105],"directly":[85],"used":[86],"training,":[88],"are":[89],"created":[90],"a":[92,135,161],"fully":[93],"pipeline":[95],"raw":[98],"data.":[99],"Furthermore,":[100],"process":[103],"customized":[106],"adapt":[108],"datasets":[110,142,174],"specific":[112],"tasks":[113],"as":[114,116,149,151],"well":[115,150],"optimized":[117],"according":[118],"characteristics":[122],"source.":[125],"We":[126],"show":[127],"that":[128],"automatically":[130],"generated":[131],"dataset":[132],"reach":[134],"comparable":[136],"level":[137],"current":[140],"open":[141],"quantity":[146],"instances":[148],"diversity":[153],"categories.":[155],"All":[156],"achieved":[159],"few":[162],"hours":[163],"without":[164],"intervention":[166],"or":[167],"costs":[168],"annotation.":[170],"Experiments":[171],"multiple":[173],"including":[175],"comparison":[177],"manually":[179],"annotated":[180],"demonstrate":[182],"potential":[184],"proposed":[187],"approach.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}