{"id":"https://openalex.org/W7163032137","doi":"https://doi.org/10.1109/access.2026.3698869","title":"Robust Lightweight Crack Classification for Real-Time AAV Bridge Inspection","display_name":"Robust Lightweight Crack Classification for Real-Time AAV Bridge Inspection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7163032137","doi":"https://doi.org/10.1109/access.2026.3698869"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3698869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3698869","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3698869","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135576998","display_name":"Wei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103140","display_name":"CCCC Highway Consultants (China)","ror":"https://ror.org/01bs84e19","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103140"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0009-8534-6150","affiliations":[{"raw_affiliation_string":"Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210103140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065859286","display_name":"Hui Li","orcid":"https://orcid.org/0000-0001-9198-3951"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haisheng Li","raw_affiliation_strings":["Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137559858","display_name":"Weijie Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103140","display_name":"CCCC Highway Consultants (China)","ror":"https://ror.org/01bs84e19","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103140"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijie Li","raw_affiliation_strings":["Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210103140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108047889","display_name":"Yi-Xiang Wang","orcid":"https://orcid.org/0000-0001-5697-0717"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiandong Wang","raw_affiliation_strings":["Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081025566","display_name":"Kaichen Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103140","display_name":"CCCC Highway Consultants (China)","ror":"https://ror.org/01bs84e19","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103140"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaichen Ma","raw_affiliation_strings":["Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Greater Bay Area Super Bridge Maintenance Technology Center, Guangdong Provincial Highway Construction Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210103140"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103925988","display_name":"Lin Yang","orcid":"https://orcid.org/0000-0001-9306-2056"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luming Yang","raw_affiliation_strings":["Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong AIHISUN Technology Company Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64192588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"97790","last_page":"97802"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.8618000149726868,"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":0.8618000149726868,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.052000001072883606,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.013199999928474426,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/bridge","display_name":"Bridge (graph theory)","score":0.574999988079071},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.36739999055862427},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.28459998965263367},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2312999963760376},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.22619999945163727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6664999723434448},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.574999988079071},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.36739999055862427},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.3626999855041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29120001196861267},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2312999963760376},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.22619999945163727},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.22499999403953552}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3698869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3698869","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6537fdd7e8b54983943cc07f0ce04889","is_oa":false,"landing_page_url":"https://doaj.org/article/6537fdd7e8b54983943cc07f0ce04889","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,"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":"IEEE Access, Vol 14, Pp 97790-97802 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3698869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3698869","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,106,113,132,135,139,153,158],"widespread":[2],"application":[3],"of":[4,67,120],"Unmanned":[5],"Aerial":[6],"Vehicles":[7],"(UAVs)":[8],"in":[9,191],"bridge":[10,108,193],"structural":[11],"health":[12],"monitoring,":[13],"deep":[14],"learning-based":[15],"automatic":[16],"crack":[17,35,168],"detection":[18],"has":[19],"become":[20],"a":[21,59,71,75,86,174,183],"major":[22],"research":[23],"focus.":[24],"However,":[25],"practical":[26,48,184],"UAV":[27,49,192],"inspections":[28],"still":[29],"face":[30],"four":[31,68],"key":[32],"challenges:":[33],"weak":[34],"features,":[36],"degraded":[37],"imaging":[38],"conditions,":[39],"severe":[40],"class":[41,102],"imbalance,":[42],"and":[43,83,95,127,143,180],"limited":[44],"computational":[45],"resources":[46],"for":[47,81,98,186],"inspection":[50],"workflows.":[51],"To":[52],"address":[53],"these":[54],"issues,":[55],"this":[56,171],"paper":[57],"proposes":[58],"unified":[60],"lightweight":[61,72],"convolutional":[62],"neural":[63],"network":[64],"framework":[65,137],"composed":[66],"synergistic":[69],"components:":[70],"backbone":[73],"network,":[74],"Convolutional":[76],"Block":[77],"Attention":[78],"Module":[79],"(CBAM)":[80],"channel":[82],"spatial":[84],"enhancement,":[85],"directed":[87],"robust":[88],"augmentation":[89],"strategy":[90],"based":[91],"on":[92,105],"inspection-scene":[93],"priors,":[94],"Focal":[96],"Loss":[97],"hard-sample":[99],"learning":[100],"under":[101],"imbalance.":[103],"Experiments":[104],"SDNET2018":[107],"deck":[109],"dataset":[110],"show":[111],"that":[112,152],"proposed":[114],"method":[115],"achieves":[116,173],"an":[117],"inference":[118],"speed":[119],"825":[121],"FPS":[122],"with":[123,131],"only":[124],"11.21M":[125],"parameters":[126],"1.82G":[128],"FLOPs.":[129],"Compared":[130],"baseline":[133],"model,":[134],"complete":[136],"improves":[138],"F1-score":[140],"by":[141,145],"2.51%":[142],"recall":[144],"3.95%.":[146],"In":[147],"addition,":[148],"Grad-CAM":[149],"visualizations":[150],"indicate":[151],"introduced":[154],"attention":[155],"module":[156],"shifts":[157],"model\u2019s":[159],"focus":[160],"from":[161],"scattered":[162],"regions":[163],"to":[164],"precise":[165],"tracking":[166],"along":[167],"trajectories.":[169],"Overall,":[170],"study":[172],"strong":[175],"balance":[176],"among":[177],"accuracy,":[178],"speed,":[179],"robustness,":[181],"providing":[182],"solution":[185],"ground-station":[187],"assisted":[188],"real-time":[189],"deployment":[190],"inspections.":[194],"The":[195],"source":[196],"code":[197],"is":[198],"available":[199],"at:":[200],"https://github.com/skylynf/AttXNet.":[201]},"counts_by_year":[],"updated_date":"2026-07-04T06:09:54.619538","created_date":"2026-06-02T00:00:00"}