{"id":"https://openalex.org/W4392024440","doi":"https://doi.org/10.1109/access.2024.3368376","title":"On Enhancing Crack Semantic Segmentation Using StyleGAN and Brownian Bridge Diffusion","display_name":"On Enhancing Crack Semantic Segmentation Using StyleGAN and Brownian Bridge Diffusion","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392024440","doi":"https://doi.org/10.1109/access.2024.3368376"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3368376","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3368376","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.2024.3368376","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093976541","display_name":"Collins C. Rakowski","orcid":"https://orcid.org/0009-0004-0548-5614"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Collins C. Rakowski","raw_affiliation_strings":["College of Engineering, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0009-0004-0548-5614","affiliations":[{"raw_affiliation_string":"College of Engineering, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056462004","display_name":"Thirimachos Bourlai","orcid":"https://orcid.org/0000-0001-8751-0836"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thirimachos Bourlai","raw_affiliation_strings":["College of Engineering, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8751-0836","affiliations":[{"raw_affiliation_string":"College of Engineering, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9007,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.83084247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"34769","last_page":"34784"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9839000105857849,"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"}},{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.98089998960495,"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":0.6407443284988403},{"id":"https://openalex.org/keywords/brownian-bridge","display_name":"Brownian bridge","score":0.5437338352203369},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.5394530892372131},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5155284404754639},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.49049705266952515},{"id":"https://openalex.org/keywords/brownian-motion","display_name":"Brownian motion","score":0.4215027689933777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4050680994987488},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15974408388137817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14578402042388916},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11492174863815308},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.07218238711357117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407443284988403},{"id":"https://openalex.org/C78651780","wikidata":"https://www.wikidata.org/wiki/Q628309","display_name":"Brownian bridge","level":3,"score":0.5437338352203369},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.5394530892372131},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5155284404754639},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.49049705266952515},{"id":"https://openalex.org/C112401455","wikidata":"https://www.wikidata.org/wiki/Q178036","display_name":"Brownian motion","level":2,"score":0.4215027689933777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4050680994987488},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15974408388137817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14578402042388916},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11492174863815308},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.07218238711357117},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3368376","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3368376","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:a34660efe9974f00917ddf4aa5be6510","is_oa":true,"landing_page_url":"https://doaj.org/article/a34660efe9974f00917ddf4aa5be6510","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 34769-34784 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3368376","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3368376","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W80253515","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2226255814","https://openalex.org/W2293021890","https://openalex.org/W2407692387","https://openalex.org/W2511065100","https://openalex.org/W2531409750","https://openalex.org/W2618530766","https://openalex.org/W2787091153","https://openalex.org/W2912350898","https://openalex.org/W2963073614","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2964308596","https://openalex.org/W2974825848","https://openalex.org/W2979396152","https://openalex.org/W2993235622","https://openalex.org/W3004052770","https://openalex.org/W3005498204","https://openalex.org/W3008832470","https://openalex.org/W3011200270","https://openalex.org/W3011690230","https://openalex.org/W3015748209","https://openalex.org/W3036669348","https://openalex.org/W3036991312","https://openalex.org/W3042900698","https://openalex.org/W3080355920","https://openalex.org/W3087277009","https://openalex.org/W3099564553","https://openalex.org/W3127751679","https://openalex.org/W3138786441","https://openalex.org/W3163273160","https://openalex.org/W3173780596","https://openalex.org/W3174807077","https://openalex.org/W3180719857","https://openalex.org/W3192378566","https://openalex.org/W3197911091","https://openalex.org/W3198911825","https://openalex.org/W3199054352","https://openalex.org/W3205191178","https://openalex.org/W3205511895","https://openalex.org/W4280626505","https://openalex.org/W4288281368","https://openalex.org/W4293241557","https://openalex.org/W4293584584","https://openalex.org/W4296714033","https://openalex.org/W4308093941","https://openalex.org/W4311083504","https://openalex.org/W4312070099","https://openalex.org/W4312933868","https://openalex.org/W4362453650","https://openalex.org/W4366742337","https://openalex.org/W4383100369","https://openalex.org/W4386076617","https://openalex.org/W4387210975","https://openalex.org/W6637373629","https://openalex.org/W6750227808","https://openalex.org/W6762718338","https://openalex.org/W6766313662","https://openalex.org/W6775956396","https://openalex.org/W6795288823","https://openalex.org/W6810595431","https://openalex.org/W6867947569"],"related_works":["https://openalex.org/W1501776718","https://openalex.org/W2615136228","https://openalex.org/W657108774","https://openalex.org/W2025535014","https://openalex.org/W2390192952","https://openalex.org/W2480620430","https://openalex.org/W4309939859","https://openalex.org/W122899020","https://openalex.org/W2529128960","https://openalex.org/W2065916337"],"abstract_inverted_index":{"Inspection":[0],"for":[1,11,109,158,265,297],"cracks":[2],"is":[3,44,114,144,156],"an":[4,22,211],"essential":[5],"yet":[6,132],"labor-intensive":[7],"aspect":[8],"of":[9,24,31,36,51,91,100,182,213,226,245,282,290],"maintenance":[10],"structures":[12],"in":[13,104,163,248,280],"active":[14],"service":[15],"bridges.":[16],"Deep":[17],"learning":[18,107],"networks,":[19],"combined":[20],"with":[21,172,179],"abundance":[23],"segmented":[25],"image":[26,295],"data":[27,43,67,103,184],"representing":[28],"various":[29],"types":[30],"cracks,":[32],"enable":[33],"the":[34,78,97,117,201,206,243],"development":[35],"a":[37,48,58,86,120,130,151,160,180,219,236,262,287],"computer":[38],"vision-based":[39],"solution.":[40],"Often,":[41],"segmentation":[42,72,102,122,138,196,255,300],"scarce":[45],"and":[46,69,77,88,146,176,190,257],"requires":[47],"great":[49],"deal":[50],"time":[52],"to":[53,61,84,136,193,200],"annotate.":[54],"This":[55],"paper":[56],"introduces":[57],"novel":[59],"approach":[60,274],"structural":[62,93],"crack":[63,94,110,195],"detection":[64],"using":[65],"synthetic":[66,92,174,294],"generation":[68,296],"advanced":[70],"semantic":[71,121,254,299],"models.":[73],"We":[74,240],"employ":[75],"StyleGAN3":[76],"Brownian":[79],"Bridge":[80],"Diffusion":[81],"Model":[82],"(BBDM)":[83],"create":[85],"diverse":[87],"realistic":[89],"dataset":[90],"images,":[95],"addressing":[96],"critical":[98],"challenge":[99],"creating":[101],"training":[105],"deep":[106],"models":[108,247],"detection.":[111],"Our":[112],"methodology":[113],"based":[115],"upon":[116],"DeepLabV3+,":[118],"i.e.,":[119],"architecture":[123],"that":[124,209,252,272],"builds":[125],"on":[126,205,231],"DeepLabv3":[127],"by":[128],"adding":[129],"simple":[131],"effective":[133],"decoder":[134],"module":[135],"enhance":[137],"results.":[139],"The":[140,269],"original":[141],"DeepLabV3+":[142],"model":[143,267],"insufficient":[145],"thus,":[147],"we":[148,167],"first":[149],"perform":[150],"meticulous":[152],"hyperparameter":[153],"tuning,":[154],"which":[155],"responsible":[157],"about":[159],"10%":[161],"increase":[162],"overall":[164],"performance.":[165,197,301],"Next,":[166],"generate":[168],"multiple":[169,232],"image-to-image":[170],"translations":[171],"BBDMs":[173],"datasets":[175,251],"pair":[177],"them":[178],"set":[181],"fine-selected":[183],"augmentation":[185,260],"techniques,":[186],"including":[187],"motion,":[188],"zoom,":[189],"defocus":[191],"blur,":[192],"improve":[194],"When":[198],"compared":[199],"state-of-the-art":[202],"latest":[203],"work":[204,217],"same":[207],"database":[208],"achieved":[210],"accuracy":[212,225,256],"61.49%,":[214],"our":[215,273],"proposed":[216],"attains":[218],"Mean":[220],"Intersection":[221],"over":[222],"Union":[223],"(MeanIoU)":[224],"65.62%":[227],"through":[228],"ensemble":[229],"modeling":[230],"synthesized":[233],"datasets,":[234],"employing":[235],"majority":[237],"voting":[238],"strategy.":[239],"also":[241,285],"showcase":[242],"potential":[244],"diffusion":[246],"synthetically":[249],"generated":[250],"elevate":[253],"introduce":[258],"blur":[259],"as":[261],"viable":[263],"technique":[264],"enhancing":[266],"robustness.":[268],"results":[270],"indicate":[271],"not":[275],"only":[276],"surpasses":[277],"conventional":[278],"methods":[279],"terms":[281],"MeanIoU":[283],"but":[284],"offers":[286],"new":[288],"avenue":[289],"research":[291],"into":[292],"diffusion-model-based":[293],"improved":[298]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}