{"id":"https://openalex.org/W4392167764","doi":"https://doi.org/10.3390/s24051467","title":"PCTC-Net: A Crack Segmentation Network with Parallel Dual Encoder Network Fusing Pre-Conv-Based Transformers and Convolutional Neural Networks","display_name":"PCTC-Net: A Crack Segmentation Network with Parallel Dual Encoder Network Fusing Pre-Conv-Based Transformers and Convolutional Neural Networks","publication_year":2024,"publication_date":"2024-02-24","ids":{"openalex":"https://openalex.org/W4392167764","doi":"https://doi.org/10.3390/s24051467","pmid":"https://pubmed.ncbi.nlm.nih.gov/38475003"},"language":"en","primary_location":{"id":"doi:10.3390/s24051467","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24051467","pdf_url":"https://www.mdpi.com/1424-8220/24/5/1467/pdf?version=1708756737","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/5/1467/pdf?version=1708756737","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052712180","display_name":"Jihwan Moon","orcid":"https://orcid.org/0000-0002-9812-7768"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ji-Hwan Moon","raw_affiliation_strings":["Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027716484","display_name":"Gyu Ho Choi","orcid":"https://orcid.org/0000-0002-8435-6068"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyuho Choi","raw_affiliation_strings":["Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-8435-6068","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071732562","display_name":"Yu-Hwan Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yu-Hwan Kim","raw_affiliation_strings":["Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084043021","display_name":"Won-Yeol Kim","orcid":"https://orcid.org/0000-0002-3492-6413"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Won-Yeol Kim","raw_affiliation_strings":["Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-3492-6413","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Engineering, Chosun University, Gwangju 61452, Republic of Korea","institution_ids":["https://openalex.org/I152238500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084043021"],"corresponding_institution_ids":["https://openalex.org/I152238500"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.8159,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82166858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"24","issue":"5","first_page":"1467","last_page":"1467"},"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":0.9925000071525574,"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":0.9912999868392944,"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/computer-science","display_name":"Computer science","score":0.6853675246238708},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6651268005371094},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6457371115684509},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6092857718467712},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5773864388465881},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5520548820495605},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46681639552116394},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4321085512638092},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3354898691177368},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32093268632888794},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20327100157737732},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.13605263829231262}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6853675246238708},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6651268005371094},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6457371115684509},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6092857718467712},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5773864388465881},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5520548820495605},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46681639552116394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4321085512638092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3354898691177368},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32093268632888794},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20327100157737732},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.13605263829231262},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24051467","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24051467","pdf_url":"https://www.mdpi.com/1424-8220/24/5/1467/pdf?version=1708756737","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38475003","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38475003","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,"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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10934755","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10934755","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10934755/pdf/sensors-24-01467.pdf","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:da45c6add16b409ea1f8edc1d1236574","is_oa":true,"landing_page_url":"https://doaj.org/article/da45c6add16b409ea1f8edc1d1236574","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":"Sensors, Vol 24, Iss 5, p 1467 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24051467","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24051467","pdf_url":"https://www.mdpi.com/1424-8220/24/5/1467/pdf?version=1708756737","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392167764.pdf","grobid_xml":"https://content.openalex.org/works/W4392167764.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W78381488","https://openalex.org/W1536729381","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2128880484","https://openalex.org/W2194775991","https://openalex.org/W2598457882","https://openalex.org/W2778653980","https://openalex.org/W2912350898","https://openalex.org/W2913930668","https://openalex.org/W2922073063","https://openalex.org/W2963043051","https://openalex.org/W2963163009","https://openalex.org/W2963881378","https://openalex.org/W2964308596","https://openalex.org/W2995177923","https://openalex.org/W2999795060","https://openalex.org/W3011076052","https://openalex.org/W3033281326","https://openalex.org/W3034502973","https://openalex.org/W3038091703","https://openalex.org/W3104567893","https://openalex.org/W3112139896","https://openalex.org/W3124942917","https://openalex.org/W3160412534","https://openalex.org/W3170841864","https://openalex.org/W3175227919","https://openalex.org/W3204197025","https://openalex.org/W3211490618","https://openalex.org/W4200015473","https://openalex.org/W4206706211","https://openalex.org/W4213019189","https://openalex.org/W4213099919","https://openalex.org/W4220771488","https://openalex.org/W4224244676","https://openalex.org/W4226085666","https://openalex.org/W4294672469","https://openalex.org/W4320036807","https://openalex.org/W4368352560","https://openalex.org/W4385245566","https://openalex.org/W4387479606","https://openalex.org/W4389161523","https://openalex.org/W6684665197","https://openalex.org/W6739901393","https://openalex.org/W6760744617","https://openalex.org/W6773120864","https://openalex.org/W6797235774","https://openalex.org/W6797399245"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W4321487865","https://openalex.org/W3155418658","https://openalex.org/W4243199227"],"abstract_inverted_index":{"Cracks":[0],"are":[1,28,80],"common":[2],"defects":[3],"that":[4,20,149],"occur":[5],"on":[6,47],"the":[7,64,127,130,139,161],"surfaces":[8],"of":[9,87,129],"objects":[10],"and":[11,52,60,108,142,157],"structures.":[12],"Crack":[13],"detection":[14],"is":[15,66,91],"a":[16,84,100,122],"critical":[17],"maintenance":[18],"task":[19],"traditionally":[21],"requires":[22],"manual":[23,26],"labor.":[24],"Large-scale":[25],"inspections":[27],"expensive.":[29],"Research":[30],"has":[31,54],"been":[32,55],"conducted":[33],"to":[34,69],"replace":[35],"expensive":[36],"human":[37],"labor":[38],"with":[39,121,138],"cheaper":[40],"computing":[41],"resources.":[42],"Recently,":[43],"crack":[44,78,89],"segmentation":[45,79],"based":[46],"convolutional":[48,109],"neural":[49,110],"networks":[50,111],"(CNNs)":[51],"transformers":[53],"actively":[56],"investigated":[57],"for":[58,77],"local":[59],"global":[61],"information.":[62],"However,":[63],"transformer":[65],"data-intensive":[67,96],"owing":[68],"its":[70],"weak":[71],"inductive":[72],"bias.":[73],"Existing":[74],"labeled":[75],"datasets":[76],"relatively":[81],"small.":[82],"Additionally,":[83],"limited":[85],"amount":[86],"fine-grained":[88],"data":[90],"available.":[92],"To":[93],"address":[94],"this":[95],"problem,":[97],"we":[98],"propose":[99],"parallel":[101],"dual":[102],"encoder":[103],"network":[104],"fusing":[105],"Pre-Conv-based":[106],"Transformers":[107],"(PCTC-Net).":[112],"The":[113,132,145],"Pre-Conv":[114],"module":[115],"automatically":[116],"optimizes":[117],"each":[118],"color":[119],"channel":[120],"small":[123],"spatial":[124],"kernel":[125],"before":[126],"input":[128],"transformer.":[131],"proposed":[133],"model,":[134],"PCTC-Net,":[135],"was":[136],"tested":[137],"DeepCrack,":[140],"Crack500,":[141],"Crackseg9k":[143],"datasets.":[144],"experimental":[146],"results":[147],"showed":[148],"our":[150],"model":[151,163],"achieved":[152],"higher":[153],"generalization":[154],"performance,":[155],"stability,":[156],"F1":[158],"scores":[159],"than":[160],"SOTA":[162],"DTrC-Net.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}