{"id":"https://openalex.org/W3029630064","doi":"https://doi.org/10.1145/3383972.3384056","title":"Recognition Method of Road Cracks with Lane Lines Based on Deep Learning","display_name":"Recognition Method of Road Cracks with Lane Lines Based on Deep Learning","publication_year":2020,"publication_date":"2020-02-15","ids":{"openalex":"https://openalex.org/W3029630064","doi":"https://doi.org/10.1145/3383972.3384056","mag":"3029630064"},"language":"en","primary_location":{"id":"doi:10.1145/3383972.3384056","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","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/A5103095722","display_name":"Renyi Chen","orcid":"https://orcid.org/0000-0001-8475-8633"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renyi Chen","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091767796","display_name":"Guosheng Xu","orcid":"https://orcid.org/0000-0002-3310-926X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guosheng Xu","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025624671","display_name":"Lin Yan","orcid":"https://orcid.org/0000-0001-7017-0329"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Lin","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102002679","display_name":"Guoai Xu","orcid":"https://orcid.org/0000-0002-9582-0698"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoai Xu","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100376455","display_name":"Miao Zhang","orcid":"https://orcid.org/0000-0001-9428-0573"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miao Zhang","raw_affiliation_strings":["School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, People's Republic of China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":null,"first_page":"379","last_page":"383"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9995999932289124,"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":0.9995999932289124,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9955999851226807,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.6192491054534912},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.6041122674942017},{"id":"https://openalex.org/keywords/abrasion","display_name":"Abrasion (mechanical)","score":0.5949040651321411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5740498900413513},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5105780363082886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48470139503479004},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4510079622268677},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3606477975845337},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22778204083442688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10921835899353027},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.07643091678619385},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07087883353233337}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192491054534912},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.6041122674942017},{"id":"https://openalex.org/C118231568","wikidata":"https://www.wikidata.org/wiki/Q3819233","display_name":"Abrasion (mechanical)","level":2,"score":0.5949040651321411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5740498900413513},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5105780363082886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48470139503479004},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4510079622268677},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3606477975845337},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22778204083442688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10921835899353027},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.07643091678619385},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07087883353233337},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383972.3384056","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383972.3384056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 12th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2069223289","https://openalex.org/W2145023731","https://openalex.org/W2352017970","https://openalex.org/W2388907576","https://openalex.org/W2511482214","https://openalex.org/W2897267929","https://openalex.org/W2964332990","https://openalex.org/W2970332685"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2017733316","https://openalex.org/W2732689006","https://openalex.org/W2290807717","https://openalex.org/W4300947998","https://openalex.org/W1550454689","https://openalex.org/W2248318657","https://openalex.org/W2444278887","https://openalex.org/W2387472657","https://openalex.org/W2611989081"],"abstract_inverted_index":{"Due":[0],"to":[1,72,119],"the":[2,7,10,17,23,26,34,38,42,74,103,113,121,131],"vehicle":[3],"wheeling":[4],"and":[5,59,80,92,112],"abrasion,":[6],"paint":[8,27],"on":[9,53],"lane":[11,48,63,114],"lines":[12,64],"usually":[13],"appears":[14],"cracked.":[15],"In":[16],"process":[18],"of":[19,22,41,62,76,87,124],"automatic":[20],"detection":[21,50],"pavement":[24,43,125],"cracks,":[25,36,126],"cracks":[28],"can":[29],"be":[30],"easily":[31],"misidentified":[32],"as":[33],"road":[35],"reducing":[37],"recognition":[39,122],"accuracy":[40],"cracks.":[44],"We":[45],"propose":[46],"a":[47,85],"line":[49,115],"method":[51,83],"based":[52],"deep":[54],"learning":[55],"method,":[56],"extracting":[57],"multi-angle":[58],"multidimensional":[60],"features":[61],"automatically.":[65],"A":[66],"complete":[67],"dataset":[68],"has":[69],"been":[70],"constructed":[71],"solve":[73],"problems":[75],"uneven":[77],"illumination,":[78],"pollution":[79],"abrasion.":[81],"Our":[82],"achieves":[84],"result":[86],"91.84%":[88],"precision,":[89],"86.67%":[90],"recall":[91],"87.34%":[93],"Dice":[94],"coefficient,":[95],"which":[96,127],"are":[97,117],"all":[98],"about":[99],"30%":[100],"better":[101,129],"than":[102,130],"traditional":[104],"digital":[105],"image":[106],"processing":[107],"techniques.":[108],"The":[109],"crack":[110,133],"model":[111,116],"superimposed":[118],"improve":[120],"effect":[123],"is":[128],"single":[132],"model.":[134]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
