{"id":"https://openalex.org/W3007763722","doi":"https://doi.org/10.1109/mits.2019.2926370","title":"Learning to Automatically Catch Potholes in Worldwide Road Scene Images","display_name":"Learning to Automatically Catch Potholes in Worldwide Road Scene Images","publication_year":2020,"publication_date":"2020-02-21","ids":{"openalex":"https://openalex.org/W3007763722","doi":"https://doi.org/10.1109/mits.2019.2926370","mag":"3007763722"},"language":"en","primary_location":{"id":"doi:10.1109/mits.2019.2926370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2019.2926370","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.07986","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"J. Javier Yebes","orcid":"https://orcid.org/0000-0002-3028-9525"},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"J. Javier Yebes","raw_affiliation_strings":["Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain"],"raw_orcid":"https://orcid.org/0000-0002-3028-9525","affiliations":[{"raw_affiliation_string":"Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain","institution_ids":["https://openalex.org/I4210092551"]}]},{"author_position":"middle","author":{"id":null,"display_name":"David Montero","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Montero","raw_affiliation_strings":["Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain","institution_ids":["https://openalex.org/I4210092551"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ignacio Arriola","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092551","display_name":"Vicomtech","ror":"https://ror.org/0023sah13","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210092551"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ignacio Arriola","raw_affiliation_strings":["Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transport Systems and Engineering, Vicomtech, San Sebastian, Guipuzcoa, Spain","institution_ids":["https://openalex.org/I4210092551"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210092551"],"apc_list":null,"apc_paid":null,"fwci":1.0028,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.72949164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"13","issue":"3","first_page":"192","last_page":"205"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9782000184059143,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9782000184059143,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.011300000362098217,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.0012000000569969416,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pothole","display_name":"Pothole (geology)","score":0.991100013256073},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6055999994277954},{"id":"https://openalex.org/keywords/flagging","display_name":"Flagging","score":0.5813000202178955},{"id":"https://openalex.org/keywords/autopilot","display_name":"Autopilot","score":0.5764999985694885},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.4814000129699707},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4578999876976013},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.4043000042438507},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39500001072883606}],"concepts":[{"id":"https://openalex.org/C2776023743","wikidata":"https://www.wikidata.org/wiki/Q7234907","display_name":"Pothole (geology)","level":2,"score":0.991100013256073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619700014591217},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6055999994277954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.600600004196167},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.5813000202178955},{"id":"https://openalex.org/C18020424","wikidata":"https://www.wikidata.org/wiki/Q220858","display_name":"Autopilot","level":2,"score":0.5764999985694885},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43650001287460327},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.4043000042438507},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2720000147819519},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mits.2019.2926370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2019.2926370","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2105.07986","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07986","pdf_url":"https://arxiv.org/pdf/2105.07986","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.07986","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.07986","pdf_url":"https://arxiv.org/pdf/2105.07986","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6191926860","display_name":null,"funder_award_id":"grant agreement no. 731993","funder_id":"https://openalex.org/F4320338335","funder_display_name":"H2020 European Research Council"}],"funders":[{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W835534642","https://openalex.org/W1536680647","https://openalex.org/W1849205593","https://openalex.org/W1963679247","https://openalex.org/W1977324115","https://openalex.org/W1998372407","https://openalex.org/W2019496031","https://openalex.org/W2028113506","https://openalex.org/W2073921079","https://openalex.org/W2101765566","https://openalex.org/W2168356304","https://openalex.org/W2172941934","https://openalex.org/W2248789019","https://openalex.org/W2331994864","https://openalex.org/W2508695265","https://openalex.org/W2547950870","https://openalex.org/W2552988497","https://openalex.org/W2557728737","https://openalex.org/W2573544122","https://openalex.org/W2604155477","https://openalex.org/W2618530766","https://openalex.org/W2735743304","https://openalex.org/W2741920276","https://openalex.org/W2795083853","https://openalex.org/W2795287407","https://openalex.org/W6686547629","https://openalex.org/W6785652829"],"related_works":[],"abstract_inverted_index":{"Among":[0],"several":[1],"road":[2,57,91],"hazards":[3,37],"that":[4],"are":[5,15],"present":[6],"in":[7,11,69,96],"any":[8],"paved":[9],"way":[10],"the":[12,18,32,47,64,74,97,133,137,163],"world,":[13,98],"potholes":[14,165],"one":[16],"of":[17,35,49,54,66,77,84,170,175],"most":[19],"annoying":[20],"and":[21,41,104,130],"involving":[22],"higher":[23],"maintenance":[24],"costs.":[25],"There":[26],"is":[27],"an":[28],"increasing":[29],"interest":[30],"on":[31,63,119,136,151],"automated":[33],"detection":[34,51,116],"these":[36],"enabled":[38],"by":[39],"technological":[40],"research":[42],"progress.":[43],"Our":[44],"work":[45],"tackled":[46],"challenge":[48],"pothole":[50,87,134],"from":[52,93],"images":[53,85],"real":[55,153],"world":[56],"scenes.":[58],"The":[59],"main":[60],"novelty":[61],"resides":[62],"application":[65],"latest":[67],"progress":[68],"Artificial":[70],"Intelligence":[71],"to":[72,161,166],"learn":[73],"visual":[75],"appearance":[76],"potholes.":[78],"We":[79,123],"built":[80],"a":[81,152,167],"large":[82],"dataset":[83],"with":[86,100],"annotations.":[88],"They":[89],"contained":[90],"scenes":[92],"different":[94,101,114],"cities":[95],"taken":[99],"cameras,":[102],"vehicles":[103],"viewpoints":[105],"under":[106],"varied":[107],"environmental":[108],"conditions.":[109],"Then,":[110],"we":[111,131],"fine-tuned":[112],"four":[113],"object":[115],"models":[117],"based":[118],"Deep":[120],"Neural":[121],"Networks.":[122],"achieved":[124],"mean":[125],"average":[126],"precision":[127],"above":[128],"75%":[129],"used":[132],"detector":[135],"Nvidia":[138],"DrivePX2":[139],"platform":[140,172],"running":[141],"at":[142,156],"5\u00e2\u0080\u00936":[143],"frames":[144],"per":[145],"second.":[146],"Moreover,":[147],"it":[148],"was":[149],"deployed":[150],"vehicle":[154],"driving":[155],"speeds":[157],"below":[158],"60":[159],"km/h":[160],"notify":[162],"detected":[164],"given":[168],"Internet":[169],"Things":[171],"as":[173],"part":[174],"AUTOPILOT":[176],"H2020":[177],"project.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2020-03-06T00:00:00"}