{"id":"https://openalex.org/W4317383279","doi":"https://doi.org/10.1109/robio55434.2022.10011748","title":"Road Defect Detection Based on Semantic Transformed Disparity Image Segmentation","display_name":"Road Defect Detection Based on Semantic Transformed Disparity Image Segmentation","publication_year":2022,"publication_date":"2022-12-05","ids":{"openalex":"https://openalex.org/W4317383279","doi":"https://doi.org/10.1109/robio55434.2022.10011748"},"language":"en","primary_location":{"id":"doi:10.1109/robio55434.2022.10011748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio55434.2022.10011748","pdf_url":null,"source":{"id":"https://openalex.org/S4363607789","display_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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/A5118941484","display_name":"Li Wang","orcid":"https://orcid.org/0009-0006-0994-9564"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Li Wang","raw_affiliation_strings":["Continental Automotive Systems (Shanghai) Co., Ltd.,Shanghai,China,201821"],"affiliations":[{"raw_affiliation_string":"Continental Automotive Systems (Shanghai) Co., Ltd.,Shanghai,China,201821","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009179586","display_name":"Wenbo Shi","orcid":"https://orcid.org/0000-0001-8834-6943"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Shi","raw_affiliation_strings":["Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037971089","display_name":"Haozhe Zhu","orcid":"https://orcid.org/0000-0002-6412-3996"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haozhe Zhu","raw_affiliation_strings":["Shanghai Qibao Dwight High School,Shanghai,China,201101"],"affiliations":[{"raw_affiliation_string":"Shanghai Qibao Dwight High School,Shanghai,China,201101","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080636157","display_name":"Denghuang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Denghuang Zhang","raw_affiliation_strings":["Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101841922","display_name":"Yikang Zhang","orcid":"https://orcid.org/0000-0002-6508-0027"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yikang Zhang","raw_affiliation_strings":["Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017685857","display_name":"Jiahe Fan","orcid":"https://orcid.org/0000-0002-2364-6811"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahe Fan","raw_affiliation_strings":["Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804"],"affiliations":[{"raw_affiliation_string":"Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,China,201804","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","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 J. Bocus","raw_affiliation_strings":["University of Bristol,Bristol,United Kingdom,BS81 UB"],"affiliations":[{"raw_affiliation_string":"University of Bristol,Bristol,United Kingdom,BS81 UB","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5118941484"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1419,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79569231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"644","last_page":"649"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9901000261306763,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7775917649269104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.737916886806488},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6687873005867004},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.6452858448028564},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5935968160629272},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5331712365150452},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.479123592376709},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4654558300971985},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4331910014152527},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4138810336589813},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.41370266675949097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39096692204475403},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10148805379867554}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7775917649269104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.737916886806488},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6687873005867004},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6452858448028564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5935968160629272},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5331712365150452},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.479123592376709},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4654558300971985},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4331910014152527},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4138810336589813},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.41370266675949097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39096692204475403},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10148805379867554},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/robio55434.2022.10011748","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio55434.2022.10011748","pdf_url":null,"source":{"id":"https://openalex.org/S4363607789","display_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire_cris_publications/2956687e-fd8f-4467-8aaa-439f75d9449b","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/2956687e-fd8f-4467-8aaa-439f75d9449b","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":"Wang, L, Shi, W, Zhu, H, Zhang, D, Zhang, Y, Fan, J & Bocus, M J 2023, Road Defect Detection Based on Semantic Transformed Disparity Image Segmentation. in 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. IEEE International Conference on Robotics and Biomimetics (ROBIO), Institute of Electrical and Electronics Engineers (IEEE), pp. 644-649. https://doi.org/10.1109/ROBIO55434.2022.10011748","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:research-information.bris.ac.uk:publications/2956687e-fd8f-4467-8aaa-439f75d9449b","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85147326646&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, L, Shi, W, Zhu, H, Zhang, D, Zhang, Y, Fan, J & Bocus, M J 2023, Road Defect Detection Based on Semantic Transformed Disparity Image Segmentation. in 2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022. IEEE International Conference on Robotics and Biomimetics (ROBIO), Institute of Electrical and Electronics Engineers (IEEE), pp. 644-649. https://doi.org/10.1109/ROBIO55434.2022.10011748","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4048178341","display_name":null,"funder_award_id":"22120220184,22120220214,2022-5-YB-08","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W83224863","https://openalex.org/W1644863801","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1965620617","https://openalex.org/W1981251392","https://openalex.org/W2013013959","https://openalex.org/W2033819227","https://openalex.org/W2033872649","https://openalex.org/W2037325199","https://openalex.org/W2069182664","https://openalex.org/W2069607360","https://openalex.org/W2107884096","https://openalex.org/W2112081648","https://openalex.org/W2117248802","https://openalex.org/W2128880484","https://openalex.org/W2143516773","https://openalex.org/W2163364417","https://openalex.org/W2769644921","https://openalex.org/W2787091153","https://openalex.org/W2792796963","https://openalex.org/W2912236777","https://openalex.org/W2919115771","https://openalex.org/W2951940080","https://openalex.org/W2963388701","https://openalex.org/W2963881378","https://openalex.org/W2969350702","https://openalex.org/W2979872609","https://openalex.org/W3048985289","https://openalex.org/W3111807772","https://openalex.org/W3119834764","https://openalex.org/W3138423360","https://openalex.org/W3176531424","https://openalex.org/W3196385186","https://openalex.org/W3199047816","https://openalex.org/W4212774693","https://openalex.org/W4225137532","https://openalex.org/W4230523054","https://openalex.org/W4317743331","https://openalex.org/W4317743348","https://openalex.org/W6683951949"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W3135697610","https://openalex.org/W4292672442","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2362101859","https://openalex.org/W2171299904","https://openalex.org/W2020803452","https://openalex.org/W2100745878","https://openalex.org/W2789598825"],"abstract_inverted_index":{"Road":[0],"defects":[1,122],"can":[2],"severely":[3],"affect":[4],"the":[5,14,19,44,141,154,164],"safety":[6],"of":[7,22,47,68,101,166],"road":[8,28,54,60,78,103,121,130,169],"users":[9],"and":[10,89,135,177,184],"vehicle":[11],"conditions.":[12],"Over":[13],"past":[15],"decade,":[16],"due":[17],"to":[18,118,162],"limited":[20],"amount":[21],"labeled":[23],"training":[24],"data,":[25],"machine":[26],"vision-based":[27],"defect":[29,55,79,170],"detection":[30,56,80,171],"approaches":[31],"have":[32,63],"been":[33],"mainly":[34],"used,":[35],"while":[36],"machine/deep":[37],"learning-based":[38],"methods":[39],"were":[40],"merely":[41],"discussed.":[42],"With":[43],"recent":[45],"development":[46],"artificial":[48],"intelligence,":[49],"convolutional":[50],"neural":[51],"network":[52],"(CNN)-based":[53],"systems":[57],"for":[58],"automated":[59],"condition":[61],"assessment":[62],"become":[64],"an":[65,106],"active":[66],"sphere":[67],"study.":[69],"In":[70],"this":[71,73],"regard,":[72],"paper":[74],"presents":[75],"a":[76,99,125],"comprehensive":[77],"system":[81],"based":[82],"on":[83],"computer":[84],"stereo":[85,102,108,136],"vision,":[86],"non-linear":[87,142],"regression,":[88],"CNN.":[90],"A":[91],"dense":[92],"disparity":[93,113,131,156],"image":[94,114],"is":[95,115],"first":[96],"estimated":[97,112],"from":[98],"pair":[100],"images":[104],"using":[105,140,153],"efficient":[107],"matching":[109],"algorithm.":[110],"The":[111,173],"then":[116],"transformed":[117,155],"better":[119],"identify":[120],"by":[123],"minimizing":[124],"global":[126],"energy":[127],"function":[128],"w.r.t.":[129],"projection":[132],"model":[133],"coefficients":[134],"rig":[137],"roll":[138],"angle,":[139],"regression":[143],"approach.":[144,172],"Finally,":[145],"three":[146],"popular":[147],"semantic":[148],"segmentation":[149],"CNNs":[150],"are":[151,160,182],"trained":[152],"images.":[157],"Extensive":[158],"experiments":[159],"conducted":[161],"demonstrate":[163],"performance":[165],"our":[167],"proposed":[168],"achieved":[174],"pixel-level":[175],"accuracy":[176],"intersection":[178],"over":[179],"union":[180],"(IoU)":[181],"98.37%":[183],"67.65%,":[185],"respectively.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}