{"id":"https://openalex.org/W7214020870","doi":"https://doi.org/10.1371/journal.pone.0358872","title":"Yolov8-CA-EYHL: A bridge crack detection algorithm based on improved YOLOv8","display_name":"Yolov8-CA-EYHL: A bridge crack detection algorithm based on improved YOLOv8","publication_year":2026,"publication_date":"2026-09-22","ids":{"openalex":"https://openalex.org/W7214020870","doi":"https://doi.org/10.1371/journal.pone.0358872","pmid":"https://pubmed.ncbi.nlm.nih.gov/42771609","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13596835"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pone.0358872","doi":"https://doi.org/10.1371/journal.pone.0358872","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0358872","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358872&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358872&type=printable","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100525621","display_name":"Xianwei Zhu","orcid":"https://orcid.org/0009-0000-6895-7376","observed_orcids":["https://orcid.org/0009-0000-6895-7376","https://orcid.org/0009-0008-0704-2365"]},"institutions":[{"id":"https://openalex.org/I4210163873","display_name":"Zhengzhou University of Industrial Technology","ror":"https://ror.org/05es8as59","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163873"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianwei Zhu","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Zhengzhou University of Industrial Technology"],"raw_orcid":"https://orcid.org/0009-0000-6895-7376","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Zhengzhou University of Industrial Technology","institution_ids":["https://openalex.org/I4210163873"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5152494421","display_name":"He Chao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210110718","display_name":"Nanyang Normal University","ror":"https://ror.org/01f7yer47","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210110718"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Chao","raw_affiliation_strings":["School of Intelligent Manufacturing and Electrical Engineering, Nanyang Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing and Electrical Engineering, Nanyang Normal University","institution_ids":["https://openalex.org/I4210110718"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yahui Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210115515","display_name":"Nanyang Institute of Technology","ror":"https://ror.org/0203c2755","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115515"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yahui Zhang","raw_affiliation_strings":["School of Intelligent Manufacturing, Nanyang Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Manufacturing, Nanyang Institute of Technology","institution_ids":["https://openalex.org/I4210115515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100525621"],"corresponding_institution_ids":["https://openalex.org/I4210163873"],"apc_list":{"value":2382,"currency":"USD","value_usd":2382},"apc_paid":{"value":2382,"currency":"USD","value_usd":2382},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60819864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":"9","first_page":"e0358872","last_page":"e0358872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bridge-crack-detection","display_name":"bridge crack detection","score":0.9980000257492065},{"id":"https://openalex.org/keywords/yolov8","display_name":"YOLOv8","score":0.9570000171661377},{"id":"https://openalex.org/keywords/coordinate-attention","display_name":"coordinate attention","score":0.9909999966621399},{"id":"https://openalex.org/keywords/multi-scale-feature-interaction","display_name":"multi-scale feature interaction","score":0.8989999890327454},{"id":"https://openalex.org/keywords/lightweight-object-detection","display_name":"lightweight object detection","score":0.6639999747276306},{"id":"https://openalex.org/keywords/infrastructure-inspection","display_name":"infrastructure inspection","score":0.5830000042915344}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7330999970436096},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6800000071525574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6739000082015991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6600000262260437},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5705000162124634},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5655999779701233},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.45590001344680786},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37869998812675476},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33980000019073486},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.26589998602867126},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2554999887943268}],"mesh":[{"descriptor_ui":"D000098432","descriptor_name":"Detection Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1371/journal.pone.0358872","doi":"https://doi.org/10.1371/journal.pone.0358872","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0358872","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358872&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},{"id":"pmid:42771609","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42771609","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PloS one","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13596835","doi":null,"is_oa":true,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42771609/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLoS One","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:f200d18862e348e39695d8ad2fd837b0","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/f200d18862e348e39695d8ad2fd837b0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"PLoS ONE, Vol 21, Iss 9, p e0358872 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1371/journal.pone.0358872","doi":"https://doi.org/10.1371/journal.pone.0358872","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0358872","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0358872&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G9000370162","display_name":null,"funder_award_id":"252300423440","funder_id":"https://openalex.org/F4320323845","funder_display_name":"Natural Science Foundation of Henan Province"}],"funders":[{"id":"https://openalex.org/F4320323845","display_name":"Natural Science Foundation of Henan Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214020870.pdf","grobid_xml":"https://content.openalex.org/works/W7214020870.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2337663571","https://openalex.org/W2399757108","https://openalex.org/W2909252127","https://openalex.org/W3016605319","https://openalex.org/W4283215527","https://openalex.org/W4360584594","https://openalex.org/W4385839827","https://openalex.org/W4389352554","https://openalex.org/W4391001683","https://openalex.org/W4400037839","https://openalex.org/W4407277378","https://openalex.org/W4408929316","https://openalex.org/W4409511558","https://openalex.org/W4410093337","https://openalex.org/W4410616658","https://openalex.org/W4413915624","https://openalex.org/W4414094279","https://openalex.org/W4414397920","https://openalex.org/W4416372079","https://openalex.org/W7130341640","https://openalex.org/W7135076033","https://openalex.org/W7140161031"],"related_works":["https://openalex.org/W7123339105","https://openalex.org/W4409511558","https://openalex.org/W4407277378","https://openalex.org/W4406300773","https://openalex.org/W7149486178","https://openalex.org/W4401628630","https://openalex.org/W7169626043","https://openalex.org/W4392132378","https://openalex.org/W4303449893","https://openalex.org/W4413361235"],"abstract_inverted_index":{"Automated":[0],"bridge":[1],"crack":[2,73],"detection":[3],"is":[4],"challenging":[5],"because":[6],"cracks":[7],"often":[8],"exhibit":[9],"weak":[10],"contrast,":[11],"irregular":[12,91],"morphology,":[13],"slender":[14,93],"structures,":[15],"and":[16,41,44,71,83,92,109,122,130,140,159,172],"strong":[17],"interference":[18],"from":[19,103],"complex":[20],"surface":[21],"textures.":[22],"To":[23],"address":[24],"these":[25],"issues,":[26],"this":[27],"study":[28],"proposes":[29],"a":[30],"YOLOv8-CA-EYHL":[31],"framework":[32],"that":[33,98],"combines":[34],"filtering-equalization":[35,50],"preprocessing":[36,108],"with":[37,128,155],"coordinate":[38],"attention":[39],"(CA)":[40],"enhanced":[42],"high-":[43],"low-frequency":[45],"feature":[46,63,81],"learning":[47],"modules.":[48],"The":[49,75,114],"strategy":[51],"improves":[52],"crack-background":[53],"contrast":[54],"while":[55,65,144],"suppressing":[56],"background":[57],"interference.":[58],"CA":[59],"enhances":[60],"spatially":[61],"directional":[62],"representation,":[64],"the":[66,88,99,104,110,170,176],"YHL":[67],"module":[68,77],"strengthens":[69],"local":[70],"high-frequency":[72],"features.":[74],"EYHL":[76],"further":[78,167],"establishes":[79],"multi-scale":[80],"interaction":[82],"spatial":[84],"recalibration":[85],"to":[86],"improve":[87],"representation":[89],"of":[90,107,120,125,149,169,175],"cracks.":[94],"Ablation":[95],"experiments":[96,154],"demonstrate":[97],"performance":[100],"improvement":[101],"results":[102],"complementary":[105],"contributions":[106],"proposed":[111,115,177],"architectural":[112],"components.":[113],"model":[116],"achieves":[117],"an":[118,123,146,162],"mAP50":[119],"93.1%":[121],"mAP50-95":[124],"63.5%,":[126],"compared":[127],"64.4%":[129],"42.8%,":[131],"respectively,":[132],"for":[133],"YOLOv8s.":[134],"It":[135],"requires":[136],"32.6":[137],"B":[138],"FLOPs":[139],"13.7":[141],"M":[142],"parameters":[143],"maintaining":[145],"inference":[147],"speed":[148],"approximately":[150],"76":[151],"FPS.":[152],"Repeated":[153],"different":[156],"random":[157],"seeds":[158],"evaluation":[160],"on":[161],"independent":[163],"external":[164],"dataset":[165],"provide":[166],"evidence":[168],"stability":[171],"generalisation":[173],"potential":[174],"framework.":[178]},"counts_by_year":[],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2026-09-23T00:00:00"}
