{"id":"https://openalex.org/W4385194766","doi":"https://doi.org/10.1109/tim.2023.3298391","title":"Multiscale Attention Networks for Pavement Defect Detection","display_name":"Multiscale Attention Networks for Pavement Defect Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385194766","doi":"https://doi.org/10.1109/tim.2023.3298391"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3298391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3298391","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5030241951","display_name":"Junde Chen","orcid":"https://orcid.org/0000-0003-1748-4374"},"institutions":[{"id":"https://openalex.org/I185071736","display_name":"Chapman University","ror":"https://ror.org/0452jzg20","country_code":"US","type":"education","lineage":["https://openalex.org/I185071736"]},{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Junde Chen","raw_affiliation_strings":["Dale E. and Sarah Ann Fowler School of Engineering, Chapman University, Orange, CA, USA","Department of Electronic Commerce, Xiangtan University, Xiangtan, China","School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-1748-4374","affiliations":[{"raw_affiliation_string":"Dale E. and Sarah Ann Fowler School of Engineering, Chapman University, Orange, CA, USA","institution_ids":["https://openalex.org/I185071736"]},{"raw_affiliation_string":"Department of Electronic Commerce, Xiangtan University, Xiangtan, China","institution_ids":["https://openalex.org/I4610292"]},{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086326544","display_name":"Yuxin Wen","orcid":"https://orcid.org/0000-0002-2352-5622"},"institutions":[{"id":"https://openalex.org/I185071736","display_name":"Chapman University","ror":"https://ror.org/0452jzg20","country_code":"US","type":"education","lineage":["https://openalex.org/I185071736"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxin Wen","raw_affiliation_strings":["Dale E. and Sarah Ann Fowler School of Engineering, Chapman University, Orange, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2352-5622","affiliations":[{"raw_affiliation_string":"Dale E. and Sarah Ann Fowler School of Engineering, Chapman University, Orange, CA, USA","institution_ids":["https://openalex.org/I185071736"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057298092","display_name":"Yaser A. Nanehkaran","orcid":"https://orcid.org/0000-0002-8055-3195"},"institutions":[{"id":"https://openalex.org/I4210141689","display_name":"Yancheng Teachers University","ror":"https://ror.org/042k5fe81","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141689"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaser Ahangari Nanehkaran","raw_affiliation_strings":["School of Information Engineering, Yancheng Teachers University, Yancheng, China"],"raw_orcid":"https://orcid.org/0000-0002-8055-3195","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Yancheng Teachers University, Yancheng, China","institution_ids":["https://openalex.org/I4210141689"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084270607","display_name":"Defu Zhang","orcid":"https://orcid.org/0000-0002-2396-1205"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defu Zhang","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-2396-1205","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086947282","display_name":"Adnan Zeb","orcid":"https://orcid.org/0000-0001-6105-3796"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Adnan Zeb","raw_affiliation_strings":["College of Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6105-3796","affiliations":[{"raw_affiliation_string":"College of Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.2362,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.99020712,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"12"},"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":0.996999979019165,"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":0.9843000173568726,"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/computer-science","display_name":"Computer science","score":0.6784405708312988},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.663521409034729},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6002901792526245},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5719771981239319},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5525590181350708},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5497995018959045},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.522411584854126},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47249189019203186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4555444121360779},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41899242997169495},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4122045338153839},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34889835119247437},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.27830755710601807}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6784405708312988},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.663521409034729},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6002901792526245},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5719771981239319},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5525590181350708},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5497995018959045},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.522411584854126},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47249189019203186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4555444121360779},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41899242997169495},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4122045338153839},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34889835119247437},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27830755710601807},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/tim.2023.3298391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3298391","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:digitalcommons.chapman.edu:engineering_articles-1182","is_oa":false,"landing_page_url":"https://digitalcommons.chapman.edu/engineering_articles/185","pdf_url":null,"source":{"id":"https://openalex.org/S4377196324","display_name":"Chapman University Digital Commons (Chapman University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I185071736","host_organization_name":"Chapman University","host_organization_lineage":["https://openalex.org/I185071736"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Engineering Faculty Articles and Research","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1259328365","display_name":null,"funder_award_id":"20720181004","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W119228284","https://openalex.org/W1516386264","https://openalex.org/W1551570072","https://openalex.org/W1901129140","https://openalex.org/W1969393996","https://openalex.org/W2008488233","https://openalex.org/W2008935780","https://openalex.org/W2014252132","https://openalex.org/W2031703128","https://openalex.org/W2124664712","https://openalex.org/W2138014601","https://openalex.org/W2144494816","https://openalex.org/W2279236905","https://openalex.org/W2407692387","https://openalex.org/W2511065100","https://openalex.org/W2560023338","https://openalex.org/W2598457882","https://openalex.org/W2612491774","https://openalex.org/W2748643398","https://openalex.org/W2752782242","https://openalex.org/W2768955070","https://openalex.org/W2786174052","https://openalex.org/W2794732825","https://openalex.org/W2804948039","https://openalex.org/W2884585870","https://openalex.org/W2898732869","https://openalex.org/W2902335457","https://openalex.org/W2912350898","https://openalex.org/W2955058313","https://openalex.org/W2963351448","https://openalex.org/W2964308596","https://openalex.org/W2979396152","https://openalex.org/W2981148440","https://openalex.org/W2981413347","https://openalex.org/W2981689412","https://openalex.org/W3034502973","https://openalex.org/W3158546727","https://openalex.org/W3168326173","https://openalex.org/W3176427953","https://openalex.org/W3177052299","https://openalex.org/W4200478585","https://openalex.org/W4220756717","https://openalex.org/W4220780913","https://openalex.org/W4282837177","https://openalex.org/W4297775537","https://openalex.org/W4317659928","https://openalex.org/W6630947148","https://openalex.org/W6639824700","https://openalex.org/W6678174250","https://openalex.org/W6737664043","https://openalex.org/W6747842307","https://openalex.org/W6753412334","https://openalex.org/W6756779378"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4390516098","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W1647606319","https://openalex.org/W4390494008","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Pavement":[0],"defects":[1,53],"such":[2],"as":[3,91],"cracks,":[4,6],"net":[5],"and":[7,19,48,55,131,141,171,200,210,223,247,267,278,284],"pit":[8],"slots":[9],"can":[10,214],"cause":[11],"potential":[12],"traffic":[13],"safety":[14],"problems.":[15],"The":[16,76,151,180,253],"timely":[17],"detection":[18,47,72,293],"identification":[20],"play":[21],"a":[22,58,250,287],"key":[23],"role":[24],"in":[25,37,45,83,112,294],"reducing":[26],"the":[27,34,71,79,86,89,92,102,106,118,121,129,136,146,163,191,207,217,234,257,264,276,281],"harm":[28],"of":[29,73,78,101,117,138,190,261,280],"various":[30],"pavement":[31,52,74,97,227,239,291],"defects.":[32,75],"Particularly,":[33],"recent":[35],"development":[36],"deep":[38],"learning-based":[39],"CNNs":[40],"has":[41],"shown":[42],"competitive":[43],"performance":[44,156],"image":[46],"classification.":[49],"To":[50],"detect":[51],"automatically":[54],"improve":[56],"effects,":[57],"multi-scale":[59,107,208],"mobile":[60],"attention-based":[61],"network,":[62],"which":[63],"we":[64],"termed":[65],"MANet,":[66,84],"is":[67,81,125,300],"proposed":[68,152,192,254,282],"to":[69,95,134],"perform":[70],"architecture":[77],"encoder-decoder":[80],"used":[82],"where":[85],"encoder":[87,130],"adopts":[88],"MobileNet":[90],"backbone":[93],"network":[94],"extract":[96,219],"defect":[98],"features.":[99],"Instead":[100],"original":[103],"3\u00d73":[104],"convolution,":[105],"convolution":[108,115,209],"kernels":[109],"are":[110],"utilized":[111],"depth-wise":[113],"separable":[114],"layers":[116],"network.":[119],"Further,":[120],"hybrid":[122,211],"attention":[123,212],"mechanism":[124],"separately":[126],"incorporated":[127],"into":[128],"decoder":[132],"modules":[133,213],"infer":[135],"significance":[137],"spatial":[139],"points":[140],"inter-channel":[142],"relationship":[143],"features":[144],"for":[145,290],"input":[147],"intermediate":[148],"feature":[149,221],"maps.":[150],"approach":[153,193,255,283],"achieves":[154,249],"state-of-the-art":[155],"on":[157,194,236,263],"two":[158,196],"publicly-available":[159],"benchmark":[160],"datasets,":[161],"i.e.,":[162],"Crack500":[164],"(500":[165],"crack":[166,174,228,240,292],"images":[167,175,241,243],"with":[168,176,244],"2,000\u00d71,500":[169],"pixels)":[170,178,246],"CFD":[172],"(118":[173],"480\u00d7320":[177],"datasets.":[179],"mean":[181],"intersection":[182],"over":[183],"union":[184],"(":[185],"<italic":[186,258],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[187,259],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">MIoU</i>":[188,260],")":[189],"these":[195],"datasets":[197],"reaches":[198],"0.7219":[199],"0.7788,":[201],"respectively.":[202],"Ablation":[203],"experiments":[204],"show":[205],"that":[206],"effectively":[215],"help":[216],"model":[218,235],"high-level":[220],"representations":[222],"generate":[224],"more":[225],"accurate":[226],"segmentation":[229],"results.":[230],"We":[231],"further":[232],"test":[233],"locally":[237],"collected":[238],"(131":[242],"1024\u00d7768":[245],"it":[248,285],"satisfactory":[251],"result.":[252],"realizes":[256],"0.6514":[262],"local":[265],"dataset":[266],"outperforms":[268],"other":[269],"compared":[270],"baseline":[271],"methods.":[272],"Experimental":[273],"findings":[274],"demonstrate":[275],"validity":[277],"feasibility":[279],"provides":[286],"viable":[288],"solution":[289],"practical":[295],"application":[296],"scenarios.":[297],"Our":[298],"code":[299],"available":[301],"at":[302],"https://github.com/xtu502/pavement-defects.":[303]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}