{"id":"https://openalex.org/W4411178819","doi":"https://doi.org/10.3390/computation13060143","title":"Precision-Driven Semantic Segmentation of Pipe Gallery Diseases Using PipeU-NetX: A Depthwise Separable Convolution Approach","display_name":"Precision-Driven Semantic Segmentation of Pipe Gallery Diseases Using PipeU-NetX: A Depthwise Separable Convolution Approach","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4411178819","doi":"https://doi.org/10.3390/computation13060143"},"language":"en","primary_location":{"id":"doi:10.3390/computation13060143","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation13060143","pdf_url":"https://www.mdpi.com/2079-3197/13/6/143/pdf?version=1749559296","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"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":"Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-3197/13/6/143/pdf?version=1749559296","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108913285","display_name":"Wenbin Song","orcid":"https://orcid.org/0000-0002-8399-7189"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbin Song","raw_affiliation_strings":["Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055224811","display_name":"Hanqian Wu","orcid":"https://orcid.org/0000-0002-1215-8919"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqian Wu","raw_affiliation_strings":["Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China"],"raw_orcid":"https://orcid.org/0000-0002-1215-8919","affiliations":[{"raw_affiliation_string":"Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030025925","display_name":"C.C. Pu","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlin Pu","raw_affiliation_strings":["Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Information Major, School of Computer Science and Engineering, Southeast University, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108913285"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10650171,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"6","first_page":"143","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.8244035243988037},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7374060153961182},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6922325491905212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.656954288482666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.523595929145813},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3861696422100067},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32349032163619995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19838988780975342},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08365869522094727}],"concepts":[{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.8244035243988037},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7374060153961182},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6922325491905212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656954288482666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.523595929145813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3861696422100067},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32349032163619995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19838988780975342},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08365869522094727},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computation13060143","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation13060143","pdf_url":"https://www.mdpi.com/2079-3197/13/6/143/pdf?version=1749559296","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"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":"Computation","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:17aaf23f947d49a9b872ba6ad4643743","is_oa":true,"landing_page_url":"https://doaj.org/article/17aaf23f947d49a9b872ba6ad4643743","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computation, Vol 13, Iss 6, p 143 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computation13060143","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation13060143","pdf_url":"https://www.mdpi.com/2079-3197/13/6/143/pdf?version=1749559296","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"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":"Computation","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411178819.pdf","grobid_xml":"https://content.openalex.org/works/W4411178819.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2103675443","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W2903623761","https://openalex.org/W3093478663","https://openalex.org/W3137911084","https://openalex.org/W3164337968","https://openalex.org/W3187589338","https://openalex.org/W4220831429","https://openalex.org/W4220943253","https://openalex.org/W4245502741","https://openalex.org/W4285294810","https://openalex.org/W4379140556","https://openalex.org/W4385739918","https://openalex.org/W4385804082","https://openalex.org/W4388287501","https://openalex.org/W4390122887","https://openalex.org/W4391265154","https://openalex.org/W4392338148","https://openalex.org/W4394601623","https://openalex.org/W4395061068","https://openalex.org/W4399557997","https://openalex.org/W6853539449","https://openalex.org/W6855082357","https://openalex.org/W6856154128"],"related_works":["https://openalex.org/W2009525028","https://openalex.org/W2530952058","https://openalex.org/W2582836483","https://openalex.org/W4299366318","https://openalex.org/W3158431807","https://openalex.org/W4297580547","https://openalex.org/W2951583185","https://openalex.org/W2531409750","https://openalex.org/W2890372105","https://openalex.org/W4308155352"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,39,52,55,62,69,73,88,105,109,114,124,145,163,167],"problems":[3],"of":[4,15,64,72,113,126,148,166],"high":[5],"labor":[6],"cost,":[7],"low":[8],"detection":[9,13,20,132],"efficiency,":[10],"and":[11,47,58,67,83,93,100,111,120,123,152,157,171],"insufficient":[12],"accuracy":[14],"traditional":[16],"pipe":[17,26,74,168],"gallery":[18,27,75,169],"disease":[19,28,76,173],"methods,":[21],"this":[22,142],"paper":[23,143],"proposes":[24],"a":[25],"segmentation":[29,71],"model,":[30],"PipeU-NetX,":[31],"based":[32],"on":[33],"deep":[34],"learning":[35],"technology.":[36],"By":[37],"introducing":[38],"innovative":[40],"down-sampling":[41],"module":[42,45,50],"MD-U,":[43],"up-sampling":[44],"SC-U,":[46],"feature":[48,56,65,150],"fusion":[49,59],"FFM,":[51],"model":[53,107,116,139],"optimizes":[54],"extraction":[57,151],"process,":[60],"reduces":[61],"loss":[63],"information,":[66],"realizes":[68],"accurate":[70,172],"image.":[77],"In":[78],"comparison":[79],"with":[80,104],"U-Net,":[81,108],"FCN,":[82],"Deeplabv3+":[84],"models,":[85],"PipeU-NetX":[86,115,138],"achieved":[87],"best":[89],"PA,":[90],"MPA,":[91],"FWIoU,":[92],"MIoU,":[94],"which":[95],"were":[96],"99.15%,":[97],"92.66%,":[98],"98.34%,":[99],"87.63%,":[101],"respectively.":[102],"Compared":[103],"benchmark":[106],"MIoU":[110],"MPA":[112],"increased":[117,134],"by":[118,129,135],"4.64%":[119],"3.92%,":[121],"respectively,":[122],"number":[125],"parameters":[127],"decreased":[128],"23.71%.":[130],"The":[131,137],"speed":[133],"22.1%.":[136],"proposed":[140],"in":[141],"shows":[144],"powerful":[146],"ability":[147],"multi-scale":[149],"defect":[153],"area":[154],"adaptive":[155],"recognition":[156],"provides":[158],"an":[159],"effective":[160],"solution":[161],"for":[162],"intelligent":[164],"monitoring":[165],"environment":[170],"segmentation.":[174]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}