{"id":"https://openalex.org/W3124067401","doi":"https://doi.org/10.1109/icpr48806.2021.9412054","title":"Aerial Road Segmentation in the Presence of Topological Label Noise","display_name":"Aerial Road Segmentation in the Presence of Topological Label Noise","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3124067401","doi":"https://doi.org/10.1109/icpr48806.2021.9412054","mag":"3124067401"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://elib.dlr.de/136343/1/Henry_et_al_Aerial_Road_Segmentation_Topological_Label_Noise.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085317653","display_name":"Corentin Henry","orcid":"https://orcid.org/0000-0002-4330-3058"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Corentin Henry","raw_affiliation_strings":["Remote Sensing Technology Institute, German Aerospace Center (DLR),Oberpfaffenhofen,Germany","Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute, German Aerospace Center (DLR),Oberpfaffenhofen,Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068079834","display_name":"Friedrich Fraundorfer","orcid":"https://orcid.org/0000-0002-5805-8892"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Friedrich Fraundorfer","raw_affiliation_strings":["Institute of Computer Graphics and Vision, Graz University of Technology (TUG),Graz,Austria","Institute of Computer Graphics and Vision, Graz University of Technology (TUG), Graz, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Graphics and Vision, Graz University of Technology (TUG),Graz,Austria","institution_ids":["https://openalex.org/I4092182"]},{"raw_affiliation_string":"Institute of Computer Graphics and Vision, Graz University of Technology (TUG), Graz, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079778751","display_name":"Eleonora Vig","orcid":"https://orcid.org/0000-0002-7015-6874"},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Eleonora Vig","raw_affiliation_strings":["Amazon,Berlin,Germany","Amazon, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon,Berlin,Germany","institution_ids":["https://openalex.org/I4210089985"]},{"raw_affiliation_string":"Amazon, Berlin, Germany","institution_ids":["https://openalex.org/I4210089985"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8222,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92916515,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2336","last_page":"2343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9995999932289124,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.9980000257492065,"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":0.7600042819976807},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7228721976280212},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6668017506599426},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5960589051246643},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5326641798019409},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44084441661834717},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4190021753311157},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3764212131500244},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32160794734954834},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3201727271080017},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12601855397224426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09645503759384155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7600042819976807},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7228721976280212},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6668017506599426},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5960589051246643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5326641798019409},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44084441661834717},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4190021753311157},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3764212131500244},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32160794734954834},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3201727271080017},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12601855397224426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09645503759384155},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:136343","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ICPR48806.2021.9412054>.","pdf_url":"https://elib.dlr.de/136343/1/Henry_et_al_Aerial_Road_Segmentation_Topological_Label_Noise.pdf","source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"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":"PeerReviewed"}],"best_oa_location":{"id":"pmh:oai:elib.dlr.de:136343","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ICPR48806.2021.9412054>.","pdf_url":"https://elib.dlr.de/136343/1/Henry_et_al_Aerial_Road_Segmentation_Topological_Label_Noise.pdf","source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"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":"PeerReviewed"},"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3124067401.pdf"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W369786348","https://openalex.org/W1677182931","https://openalex.org/W1898703532","https://openalex.org/W1901129140","https://openalex.org/W1905829557","https://openalex.org/W1975128126","https://openalex.org/W2032708784","https://openalex.org/W2121056381","https://openalex.org/W2136688338","https://openalex.org/W2144801789","https://openalex.org/W2167460663","https://openalex.org/W2194775991","https://openalex.org/W2252268321","https://openalex.org/W2559545830","https://openalex.org/W2559597482","https://openalex.org/W2595964094","https://openalex.org/W2620899671","https://openalex.org/W2623331213","https://openalex.org/W2772415238","https://openalex.org/W2780861787","https://openalex.org/W2786492053","https://openalex.org/W2798925380","https://openalex.org/W2799213142","https://openalex.org/W2804199516","https://openalex.org/W2884281986","https://openalex.org/W2889340060","https://openalex.org/W2891422174","https://openalex.org/W2893801697","https://openalex.org/W2896446634","https://openalex.org/W2900680440","https://openalex.org/W2901082355","https://openalex.org/W2911205309","https://openalex.org/W2913847772","https://openalex.org/W2921476973","https://openalex.org/W2934268922","https://openalex.org/W2952133801","https://openalex.org/W2962762541","https://openalex.org/W2962914239","https://openalex.org/W2962978395","https://openalex.org/W2963270775","https://openalex.org/W2963446712","https://openalex.org/W2964292098","https://openalex.org/W2964309882","https://openalex.org/W2964333009","https://openalex.org/W3125782078","https://openalex.org/W4289667027","https://openalex.org/W6639824700","https://openalex.org/W6691441656","https://openalex.org/W6730192449","https://openalex.org/W6748481559"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W4312417841"],"abstract_inverted_index":{"The":[0],"availability":[1],"of":[2,63,89],"large-scale":[3],"annotated":[4],"datasets":[5,44],"has":[6],"enabled":[7],"Fully-Convolutional":[8],"Neural":[9],"Networks":[10],"to":[11,27,121,131],"reach":[12],"outstanding":[13],"performance":[14],"on":[15,46,100],"road":[16,103],"extraction":[17,114,147],"in":[18,112,148],"aerial":[19],"images.":[20],"However,":[21],"high-quality":[22],"pixel-level":[23],"annotation":[24],"is":[25],"expensive":[26],"produce":[28],"and":[29,69,81,91,116,144],"even":[30],"manually":[31],"labeled":[32],"data":[33],"often":[34],"contains":[35],"topological":[36],"errors.":[37],"Trading":[38],"off":[39],"quality":[40,115,142],"for":[41,52,141],"quantity,":[42],"many":[43],"rely":[45],"already":[47],"available":[48],"yet":[49],"noisy":[50],"labels,":[51],"example":[53],"from":[54],"OpenStreetMap.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59],"explore":[60],"the":[61],"training":[62],"custom":[64],"U-Nets":[65],"built":[66],"with":[67,123],"ResNet":[68],"DenseNet":[70],"backbones":[71],"using":[72],"noise-aware":[73,92],"losses":[74,107],"that":[75],"are":[76],"robust":[77],"towards":[78],"label":[79,125],"omission":[80],"registration":[82],"noise.":[83,126],"We":[84],"perform":[85],"an":[86],"extensive":[87],"evaluation":[88],"standard":[90],"losses,":[93],"including":[94],"a":[95,109,118],"novel":[96],"Bootstrapped":[97],"DICE-Coefficient":[98],"loss,":[99],"two":[101,132],"challenging":[102],"segmentation":[104],"benchmarks.":[105],"Our":[106,127],"yield":[108],"consistent":[110],"improvement":[111],"overall":[113],"exhibit":[117],"strong":[119],"capacity":[120],"cope":[122],"severe":[124],"method":[128],"generalizes":[129],"well":[130],"other":[133],"fine-grained":[134],"topology":[135],"delineation":[136],"tasks:":[137],"surface":[138],"crack":[139],"detection":[140],"inspection":[143],"cell":[145],"membrane":[146],"electron":[149],"microscopy":[150],"imagery.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
