{"id":"https://openalex.org/W4414473089","doi":"https://doi.org/10.1061/jccee5.cpeng-6831","title":"Tunnel Crack Detection and Evaluation Based on Improved Holistically Nested Edge Detection Network","display_name":"Tunnel Crack Detection and Evaluation Based on Improved Holistically Nested Edge Detection Network","publication_year":2025,"publication_date":"2025-09-24","ids":{"openalex":"https://openalex.org/W4414473089","doi":"https://doi.org/10.1061/jccee5.cpeng-6831"},"language":"en","primary_location":{"id":"doi:10.1061/jccee5.cpeng-6831","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6831","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","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/A5058956188","display_name":"Yaodong Wang","orcid":"https://orcid.org/0000-0002-4334-8758"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaodong Wang","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101271595","display_name":"Chenhao Guo","orcid":"https://orcid.org/0009-0001-6632-7271"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhao Guo","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089713791","display_name":"Zhen Liu","orcid":"https://orcid.org/0000-0001-8762-0664"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Liu","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004264337","display_name":"Liqiang Zhu","orcid":"https://orcid.org/0000-0002-5436-6660"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqiang Zhu","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006768038","display_name":"Baoqing Guo","orcid":"https://orcid.org/0000-0002-0110-8107"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoqing Guo","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112223362","display_name":"Weizhen Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhen Zhou","raw_affiliation_strings":["Beijing Jiaotong Univ"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong Univ","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5058956188"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.0701,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80957715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"40","issue":"1","first_page":null,"last_page":null},"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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9961000084877014,"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":0.9955999851226807,"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/pyramid","display_name":"Pyramid (geometry)","score":0.5249999761581421},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.5166000127792358},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5127999782562256},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.49079999327659607},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4796999990940094},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4318000078201294},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4133000075817108},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.39959999918937683}],"concepts":[{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.5166000127792358},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5108000040054321},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.49079999327659607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4805999994277954},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4796999990940094},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40139999985694885},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3467999994754791},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30550000071525574},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.25949999690055847},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/jccee5.cpeng-6831","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6831","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W845365781","https://openalex.org/W1986526928","https://openalex.org/W2133059825","https://openalex.org/W2471813465","https://openalex.org/W2588612844","https://openalex.org/W2765854388","https://openalex.org/W2767742754","https://openalex.org/W2801439730","https://openalex.org/W2884374137","https://openalex.org/W2905163589","https://openalex.org/W2912350898","https://openalex.org/W2913910726","https://openalex.org/W2920633487","https://openalex.org/W2944991824","https://openalex.org/W2956776634","https://openalex.org/W2963351448","https://openalex.org/W2965295724","https://openalex.org/W3082043672","https://openalex.org/W3106763147","https://openalex.org/W3112984608","https://openalex.org/W3138516171","https://openalex.org/W3163259028","https://openalex.org/W3163568349","https://openalex.org/W3178744167","https://openalex.org/W3196589184","https://openalex.org/W3202439968","https://openalex.org/W3205511895","https://openalex.org/W4220952508","https://openalex.org/W4224244676","https://openalex.org/W4225302732","https://openalex.org/W4229020878","https://openalex.org/W4229021167","https://openalex.org/W4281254198","https://openalex.org/W4304617840","https://openalex.org/W4307123709","https://openalex.org/W4307296199","https://openalex.org/W4308151341","https://openalex.org/W4318989431","https://openalex.org/W4319755444","https://openalex.org/W4327715503","https://openalex.org/W4362551393","https://openalex.org/W4362597614","https://openalex.org/W4367146803","https://openalex.org/W4367838721","https://openalex.org/W4379877890","https://openalex.org/W4381660684","https://openalex.org/W4382982054","https://openalex.org/W4383961631","https://openalex.org/W4388549934","https://openalex.org/W4388630469","https://openalex.org/W4390226181","https://openalex.org/W4390295961","https://openalex.org/W4392121023","https://openalex.org/W4392167764","https://openalex.org/W4395479227","https://openalex.org/W4397033424"],"related_works":[],"abstract_inverted_index":{"Crack":[0],"detection":[1,68,85,144],"is":[2,36],"essential":[3],"for":[4,38,49,76,164,168,173],"the":[5,26,71,124,135,139],"routine":[6],"inspection":[7],"of":[8,126,149,154,162],"subway":[9,42],"tunnels.":[10],"This":[11],"study":[12],"addresses":[13],"key":[14],"challenges,":[15],"such":[16],"as":[17],"low":[18],"image":[19,62],"acquisition":[20,125],"efficiency,":[21],"poor":[22],"recognition":[23],"performance,":[24],"and":[25,30,40,52,79,105,111,116,131,151,171],"inability":[27],"to":[28,92],"quantify":[29],"evaluate":[31],"cracks.":[32],"A":[33],"novel":[34],"method":[35],"proposed":[37,140],"acquiring":[39],"detecting":[41],"tunnel":[43,66,129],"crack":[44,67,95,109,165],"images,":[45],"with":[46,60,88,145],"additional":[47],"features":[48],"parameter":[50],"calculation":[51],"risk":[53,117,120],"assessment.":[54,121],"The":[55,156],"approach":[56],"combines":[57],"deep":[58],"learning":[59],"digital":[61],"processing":[63],"in":[64],"a":[65,89,146],"system,":[69],"using":[70],"multiscale":[72],"block":[73],"(MSBlock)":[74],"module":[75],"hollow":[77],"convolution":[78],"an":[80,152],"improved":[81],"holistically":[82],"nested":[83],"edge":[84],"(HED)":[86],"network":[87],"feature":[90],"pyramid":[91],"achieve":[93],"automatic":[94],"extraction.":[96],"Postprocessing":[97],"algorithms,":[98],"including":[99],"adaptive":[100],"thresholding,":[101],"connected":[102],"component":[103],"filtering,":[104],"morphological":[106],"closing,":[107],"identify":[108],"types":[110],"compute":[112],"parameters":[113],"like":[114],"measurements":[115],"scores,":[118],"enhancing":[119],"Based":[122],"on":[123],"real":[127],"metro":[128],"images":[130],"experimental":[132],"data":[133],"analysis,":[134],"results":[136],"show":[137],"that":[138],"algorithm":[141,157],"achieves":[142],"pixel-level":[143],"mean":[147],"IoU":[148],"0.8922":[150],"accuracy":[153],"92.77%.":[155],"also":[158],"demonstrates":[159],"precision":[160],"rates":[161],"95.06%":[163],"length,":[166],"91.23%":[167],"maximum":[169],"width,":[170],"97.36%":[172],"pixel":[174],"area.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}