{"id":"https://openalex.org/W7125564773","doi":"https://doi.org/10.1061/jccee5.cpeng-7247","title":"BSCS-Net: A Lightweight Segmentation Network for Automated Bridge Surface Crack Detection","display_name":"BSCS-Net: A Lightweight Segmentation Network for Automated Bridge Surface Crack Detection","publication_year":2026,"publication_date":"2026-01-23","ids":{"openalex":"https://openalex.org/W7125564773","doi":"https://doi.org/10.1061/jccee5.cpeng-7247"},"language":"en","primary_location":{"id":"doi:10.1061/jccee5.cpeng-7247","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-7247","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/A5044296857","display_name":"Allen Zhang","orcid":"https://orcid.org/0000-0002-2565-9894"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Allen A. Zhang","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031201356","display_name":"D. W. Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingfeng Wang","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123651810","display_name":"Yi Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Peng","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114202638","display_name":"Huixuan Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huixuan Cheng","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115605034","display_name":"Yifan Wei","orcid":"https://orcid.org/0009-0007-3388-4972"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Wei","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018957083","display_name":"You Zhan","orcid":"https://orcid.org/0000-0002-9874-1100"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"You Zhan","raw_affiliation_strings":["Southwest Jiaotong Univ"],"raw_orcid":"https://orcid.org/0000-0002-9874-1100","affiliations":[{"raw_affiliation_string":"Southwest Jiaotong Univ","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044296857"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14701601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"3","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":0.9937999844551086,"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":0.9937999844551086,"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":0.0015999999595806003,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.00039999998989515007,"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/bridge","display_name":"Bridge (graph theory)","score":0.6194999814033508},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6014999747276306},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5967000126838684},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47760000824928284},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4691999852657318},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44290000200271606},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3547999858856201},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33000001311302185}],"concepts":[{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.6194999814033508},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6014999747276306},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5967000126838684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5608000159263611},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.382999986410141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3707999885082245},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3285999894142151},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30869999527931213},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2912999987602234},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2854999899864197},{"id":"https://openalex.org/C2778664469","wikidata":"https://www.wikidata.org/wiki/Q150425","display_name":"Rebar","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28060001134872437},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27630001306533813},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.26829999685287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/jccee5.cpeng-7247","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-7247","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":72,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2005750530","https://openalex.org/W2022844898","https://openalex.org/W2194775991","https://openalex.org/W2535388113","https://openalex.org/W2560023338","https://openalex.org/W2592939477","https://openalex.org/W2598457882","https://openalex.org/W2753792608","https://openalex.org/W2884585870","https://openalex.org/W2897872796","https://openalex.org/W2903163391","https://openalex.org/W2962914239","https://openalex.org/W2963881378","https://openalex.org/W2964308596","https://openalex.org/W2978183057","https://openalex.org/W2981078814","https://openalex.org/W3011200270","https://openalex.org/W3034552520","https://openalex.org/W3034864980","https://openalex.org/W3048807633","https://openalex.org/W3091882245","https://openalex.org/W3093870111","https://openalex.org/W3112798201","https://openalex.org/W3131423870","https://openalex.org/W3133394016","https://openalex.org/W3134992334","https://openalex.org/W3153045646","https://openalex.org/W3155750399","https://openalex.org/W3173780596","https://openalex.org/W4205390326","https://openalex.org/W4221062065","https://openalex.org/W4229035138","https://openalex.org/W4280493642","https://openalex.org/W4285334614","https://openalex.org/W4288057881","https://openalex.org/W4293457170","https://openalex.org/W4293527381","https://openalex.org/W4297464364","https://openalex.org/W4298143102","https://openalex.org/W4307265291","https://openalex.org/W4310506223","https://openalex.org/W4312851514","https://openalex.org/W4321232185","https://openalex.org/W4383961573","https://openalex.org/W4384299737","https://openalex.org/W4384525860","https://openalex.org/W4385391093","https://openalex.org/W4386378590","https://openalex.org/W4387940102","https://openalex.org/W4388745764","https://openalex.org/W4389496303","https://openalex.org/W4390044342","https://openalex.org/W4390661775","https://openalex.org/W4390873058","https://openalex.org/W4392843888","https://openalex.org/W4393397583","https://openalex.org/W4393994130","https://openalex.org/W4393999278","https://openalex.org/W4396825686","https://openalex.org/W4396953428","https://openalex.org/W4399489875","https://openalex.org/W4400268261","https://openalex.org/W4401520695","https://openalex.org/W4402410240","https://openalex.org/W4403828600","https://openalex.org/W4405190420","https://openalex.org/W4407867167","https://openalex.org/W4407889583","https://openalex.org/W4408069371","https://openalex.org/W4408993447","https://openalex.org/W4412785212"],"related_works":[],"abstract_inverted_index":{"Timely":[0],"detection":[1,39,89],"and":[2,17,54,64,80,111,126,140,149,162,164,170,197],"repair":[3],"of":[4,40,159,167,188],"cracks":[5,42],"play":[6],"a":[7,22,49,55,61,66,99,105,112,121,184],"critical":[8],"role":[9],"in":[10,60,77,202],"ensuring":[11],"traffic":[12],"safety":[13],"during":[14],"bridge":[15,28,101,107,203],"operation":[16],"maintenance.":[18],"This":[19,85],"paper":[20],"proposes":[21],"lightweight,":[23],"end-to-end":[24],"segmentation":[25,31,133],"network":[26,32],"named":[27],"surface":[29,41],"crack":[30,78,102,108,114],"(BSCS-Net),":[33],"designed":[34],"for":[35,199],"automated,":[36],"high-precision,":[37],"pixel-level":[38],"on":[43,98,172],"bridges.":[44],"The":[45],"proposed":[46],"BSCS-Net":[47,119,152],"integrates":[48],"hybrid":[50,56],"downsampling":[51],"module":[52,58,70],"(HDSM)":[53],"upsampling":[57],"(HUSM)":[59],"collaborative":[62],"architecture,":[63],"incorporates":[65],"parallel":[67],"spatial-channel":[68],"attention":[69],"(PSCAM)":[71],"to":[72],"enhance":[73],"the":[74,173,181],"perceptual":[75],"capability":[76],"regions":[79],"preserve":[81],"fine":[82],"edge":[83],"details.":[84],"design":[86],"significantly":[87],"improves":[88],"accuracy":[90,125],"while":[91],"reducing":[92],"model":[93,182],"complexity.":[94],"Extensive":[95],"experiments":[96],"conducted":[97],"self-built":[100],"data":[103,109,115],"set,":[104,110],"public":[106,113],"set":[116],"demonstrate":[117],"that":[118],"achieves":[120,153],"favorable":[122],"balance":[123],"between":[124],"inference":[127],"speed.":[128],"Compared":[129],"with":[130],"mainstream":[131],"semantic":[132],"networks":[134],"such":[135],"as":[136,142,144],"U-Net,":[137],"DeepLabv3+,":[138],"SegFormer,":[139],"Swin-Unet,":[141],"well":[143],"crack-specific":[145],"models":[146],"like":[147],"ShuttleNet":[148],"Mix-Graph":[150],"CrackNet,":[151],"intersection":[154],"over":[155],"union":[156],"(IoU)":[157],"scores":[158],"77.15%,":[160],"71.97%,":[161],"62.04%,":[163],"corresponding":[165],"F1-scores":[166],"87.10%,":[168],"83.70%,":[169],"76.57%":[171],"three":[174],"benchmark":[175],"test":[176],"sets,":[177],"respectively.":[178],"In":[179],"addition,":[180],"reaches":[183],"real-time":[185],"processing":[186],"speed":[187],"21.39":[189],"frames":[190],"per":[191],"second":[192],"(FPS),":[193],"demonstrating":[194],"strong":[195],"practicality":[196],"potential":[198],"large-scale":[200],"deployment":[201],"inspection":[204],"applications.":[205]},"counts_by_year":[],"updated_date":"2026-01-25T23:04:38.658462","created_date":"2026-01-24T00:00:00"}
