{"id":"https://openalex.org/W2970332685","doi":"https://doi.org/10.1109/ivs.2019.8814000","title":"Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding","display_name":"Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2970332685","doi":"https://doi.org/10.1109/ivs.2019.8814000","mag":"2970332685"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2019.8814000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2019.8814000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Vehicles Symposium (IV)","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/A5038867899","display_name":"Rui Fan","orcid":"https://orcid.org/0000-0003-2593-6596"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Rui Fan","raw_affiliation_strings":["Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082438256","display_name":"Mohammud Junaid Bocus","orcid":"https://orcid.org/0000-0001-7843-3445"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mohammud Junaid Bocus","raw_affiliation_strings":["Visual Information Institute, University of Bristol, Bristol, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Visual Information Institute, University of Bristol, Bristol, United Kingdom","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067350621","display_name":"Yilong Zhu","orcid":"https://orcid.org/0000-0001-5332-0794"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yilong Zhu","raw_affiliation_strings":["Unity-Drive Technology Inc, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Unity-Drive Technology Inc, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048730226","display_name":"Jianhao Jiao","orcid":"https://orcid.org/0000-0001-7372-266X"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jianhao Jiao","raw_affiliation_strings":["Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118941484","display_name":"Li Wang","orcid":"https://orcid.org/0009-0006-0994-9564"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["National Engineering Research Center of Road Maintenance Technologies, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Road Maintenance Technologies, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051297619","display_name":"Fulong Ma","orcid":"https://orcid.org/0000-0002-3681-9611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fulong Ma","raw_affiliation_strings":["Unity-Drive Technology Inc, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Unity-Drive Technology Inc, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107638072","display_name":"Shanshan Cheng","orcid":"https://orcid.org/0000-0002-6953-0136"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanshan Cheng","raw_affiliation_strings":["National Engineering Research Center of Road Maintenance Technologies, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Road Maintenance Technologies, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100347785","display_name":"Ming Liu","orcid":"https://orcid.org/0000-0002-4500-238X"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ming Liu","raw_affiliation_strings":["Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, Robotics Institute, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Robotics and Multi-Perception Laboratory, the Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5038867899"],"corresponding_institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":18.7531,"has_fulltext":false,"cited_by_count":213,"citation_normalized_percentile":{"value":0.99732071,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"474","last_page":"479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"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":1.0,"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":0.9955000281333923,"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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9775000214576721,"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/thresholding","display_name":"Thresholding","score":0.8483278751373291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7822459936141968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7780649065971375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6984451413154602},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5979444980621338},{"id":"https://openalex.org/keywords/road-surface","display_name":"Road surface","score":0.5706082582473755},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5624414682388306},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5567737817764282},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5440362095832825},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5242355465888977},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5095100998878479},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.457295298576355},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44953611493110657},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41482454538345337},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1681530475616455}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8483278751373291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7822459936141968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7780649065971375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6984451413154602},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5979444980621338},{"id":"https://openalex.org/C2780042925","wikidata":"https://www.wikidata.org/wiki/Q1049667","display_name":"Road surface","level":2,"score":0.5706082582473755},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5624414682388306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5567737817764282},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5440362095832825},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5242355465888977},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5095100998878479},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.457295298576355},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44953611493110657},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41482454538345337},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1681530475616455},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ivs.2019.8814000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2019.8814000","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-99023","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-99023","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"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":"Conference paper"},{"id":"pmh:oai:repository.ust.hk:1783.1-99023","is_oa":false,"landing_page_url":"http://repository.ust.hk/ir/Record/1783.1-99023","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/d4a4b5ea-b3d9-4fae-98be-0a8a52d36ce7","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/d4a4b5ea-b3d9-4fae-98be-0a8a52d36ce7","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fan, R, Bocus, M J, Zhu, Y, Jiao, J, Wang, L, Ma, F, Cheng, S & Liu, M 2019, Road crack detection using deep convolutional neural network and adaptive thresholding. in 2019 IEEE Intelligent Vehicles Symposium, IV 2019., 8814000, IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2019-June, Institute of Electrical and Electronics Engineers (IEEE), pp. 474-479. https://doi.org/10.1109/IVS.2019.8814000","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W22040386","https://openalex.org/W32111384","https://openalex.org/W164894702","https://openalex.org/W1516386264","https://openalex.org/W1582255764","https://openalex.org/W1836465849","https://openalex.org/W1871050032","https://openalex.org/W1960182310","https://openalex.org/W1967521064","https://openalex.org/W1977419602","https://openalex.org/W1990643970","https://openalex.org/W1995130521","https://openalex.org/W2002365660","https://openalex.org/W2019496031","https://openalex.org/W2020109627","https://openalex.org/W2031703128","https://openalex.org/W2031946226","https://openalex.org/W2033819500","https://openalex.org/W2059208457","https://openalex.org/W2072512222","https://openalex.org/W2074925468","https://openalex.org/W2079054397","https://openalex.org/W2133059825","https://openalex.org/W2143516773","https://openalex.org/W2144801789","https://openalex.org/W2163605009","https://openalex.org/W2166893195","https://openalex.org/W2167510172","https://openalex.org/W2172014587","https://openalex.org/W2312405072","https://openalex.org/W2511065100","https://openalex.org/W2514854142","https://openalex.org/W2553579894","https://openalex.org/W2744548708","https://openalex.org/W2792796963","https://openalex.org/W2799746312","https://openalex.org/W2810622125","https://openalex.org/W2885146443","https://openalex.org/W2887699950","https://openalex.org/W2919115771","https://openalex.org/W2949117887","https://openalex.org/W2963388701","https://openalex.org/W2966168550","https://openalex.org/W2967031855","https://openalex.org/W2971184620","https://openalex.org/W6601285894","https://openalex.org/W6606622037","https://openalex.org/W6634804536","https://openalex.org/W6684191040","https://openalex.org/W6684372118","https://openalex.org/W6685427411"],"related_works":["https://openalex.org/W2138983844","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2111883783","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2161102362"],"abstract_inverted_index":{"Crack":[0],"is":[1,18,45,54,62],"one":[2],"of":[3,88,117],"the":[4,86,96,120,127],"most":[5],"common":[6],"road":[7,12,40,97],"distresses":[8],"which":[9,44,83],"may":[10],"pose":[11],"safety":[13],"hazards.":[14],"Generally,":[15],"crack":[16,41],"detection":[17,42],"performed":[19],"by":[20],"either":[21],"certified":[22],"inspectors":[23],"or":[24,71],"structural":[25],"engineers.":[26],"This":[27],"task":[28],"is,":[29],"however,":[30],"time-consuming,":[31],"subjective":[32],"and":[33,50,119],"labor-intensive.":[34],"In":[35],"this":[36],"paper,":[37],"a":[38,57],"novel":[39],"algorithm":[43],"based":[46],"on":[47],"deep":[48,58],"learning":[49],"adaptive":[51,101],"image":[52,68],"segmentation":[53],"proposed.":[55],"Firstly,":[56],"convolutional":[59],"neural":[60],"network":[61,110],"trained":[63],"to":[64],"determine":[65],"whether":[66],"an":[67,100,115],"contains":[69],"cracks":[70,76,92,121],"not.":[72],"The":[73,104],"images":[74,113,128],"containing":[75],"are":[77,93],"then":[78],"smoothed":[79],"using":[80,99,129],"bilateral":[81],"filtering,":[82],"greatly":[84],"minimizes":[85],"number":[87],"noisy":[89],"pixels.":[90],"Finally,":[91],"extracted":[94,125],"from":[95,126],"surface":[98],"thresholding":[102,132],"method.":[103],"experimental":[105],"results":[106],"illustrate":[107],"that":[108],"our":[109,130],"can":[111,122],"classify":[112],"with":[114],"accuracy":[116],"99.92%,":[118],"be":[123],"successfully":[124],"proposed":[131],"algorithm.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":52},{"year":2023,"cited_by_count":37},{"year":2022,"cited_by_count":35},{"year":2021,"cited_by_count":31},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
