{"id":"https://openalex.org/W7084062002","doi":"https://doi.org/10.1109/yac66630.2025.11149814","title":"Channel Attention and Partial Convolution for Normalizing Flows in Power Line Defect Detection","display_name":"Channel Attention and Partial Convolution for Normalizing Flows in Power Line Defect Detection","publication_year":2025,"publication_date":"2025-05-17","ids":{"openalex":"https://openalex.org/W7084062002","doi":"https://doi.org/10.1109/yac66630.2025.11149814"},"language":"en","primary_location":{"id":"doi:10.1109/yac66630.2025.11149814","doi":"https://doi.org/10.1109/yac66630.2025.11149814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/yac66630.2025.11149814","pdf_url":null,"source":{"id":"https://openalex.org/S4363607866","display_name":"Youth Academic Annual Conference of Chinese Association of Automation (YAC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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":null,"display_name":"Zhikang Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikang Chen","raw_affiliation_strings":["Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zixuan Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Wang","raw_affiliation_strings":["Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guoao Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoao Zhou","raw_affiliation_strings":["Wuhan University of Technology,School of Automation,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Automation,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuxuan Cai","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Cai","raw_affiliation_strings":["Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Naval Architecture, Ocean and Energy Power Engineering,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006155241","display_name":"Huiwen Xia","orcid":"https://orcid.org/0009-0005-5537-7504","observed_orcids":["https://orcid.org/0009-0005-5537-7504"]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiwen Xia","raw_affiliation_strings":["Wuhan University of Technology,School of Automation,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Automation,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xixiu Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xixiu Wu","raw_affiliation_strings":["Wuhan University of Technology,School of Automation,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Automation,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59547686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1844","last_page":"1849"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.9639000296592712,"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"}},"topics":[{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.9639000296592712,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.01810000091791153,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.008299999870359898,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/normalizing-flows","display_name":"normalizing flows","score":0.8840000033378601},{"id":"https://openalex.org/keywords/partial-convolution","display_name":"partial convolution","score":0.8360000252723694},{"id":"https://openalex.org/keywords/channel-attention","display_name":"channel attention","score":0.796999990940094},{"id":"https://openalex.org/keywords/squeeze-and-excitation-network","display_name":"SENet","score":0.9129999876022339},{"id":"https://openalex.org/keywords/model-compression","display_name":"model compression","score":0.48500001430511475}],"concepts":[{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.7908999919891357},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7512000203132629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5960999727249146},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5778999924659729},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.572700023651123},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.5479999780654907},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5289000272750854},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5192999839782715},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.46709999442100525},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36820000410079956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26919999718666077},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2581000030040741},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/yac66630.2025.11149814","doi":"https://doi.org/10.1109/yac66630.2025.11149814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/yac66630.2025.11149814","pdf_url":null,"source":{"id":"https://openalex.org/S4363607866","display_name":"Youth Academic Annual Conference of Chinese Association of Automation (YAC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th Youth Academic Annual Conference of Chinese Association of Automation (YAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7207000255584717,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"sustainable_development_goals_aurora":[{"score":0.4334147870540619,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1978459068","https://openalex.org/W2018622255","https://openalex.org/W2243417253","https://openalex.org/W2550512190","https://openalex.org/W2743138268","https://openalex.org/W2752782242","https://openalex.org/W2809705434","https://openalex.org/W2907868778","https://openalex.org/W2914570111","https://openalex.org/W2951559372","https://openalex.org/W2963045681","https://openalex.org/W2966018429","https://openalex.org/W2987228832","https://openalex.org/W2994615081","https://openalex.org/W3020939972","https://openalex.org/W3031571129","https://openalex.org/W3034552520","https://openalex.org/W3081828334","https://openalex.org/W3114010851","https://openalex.org/W3169651898","https://openalex.org/W3169893408","https://openalex.org/W3173664002","https://openalex.org/W3183588514","https://openalex.org/W3184641178","https://openalex.org/W3199334903","https://openalex.org/W3204520143","https://openalex.org/W4288693944","https://openalex.org/W4309020974","https://openalex.org/W4386047745","https://openalex.org/W4389094542","https://openalex.org/W4401076751"],"related_works":[],"abstract_inverted_index":{"In":[0],"power":[1,164],"line":[2,165],"defect":[3,23,67],"detection,":[4],"due":[5],"to":[6,64],"the":[7,15,21,70,74,79,89,96,110,134,150,156],"lack":[8],"of":[9,17,160],"annotated":[10],"defective":[11],"component":[12],"images":[13],"and":[14,33,48,92,145,158],"stacking":[16],"convolutional":[18,76],"modules":[19],"in":[20,78,123],"model,":[22],"detection":[24,68],"faces":[25],"drawbacks":[26],"such":[27],"as":[28],"low":[29],"accuracy,":[30],"model":[31,139],"complexity,":[32],"computational":[34],"inefficiency.":[35],"To":[36],"address":[37],"this":[38],"issue,":[39],"a":[40,119],"novel":[41],"approach":[42],"is":[43,60,82],"presented":[44],"where":[45],"partial":[46],"convolution":[47],"Squeeze-and-Excitation":[49],"Networks":[50],"are":[51],"integrated":[52],"into":[53],"PCSENet.":[54,85],"Subsequently,":[55],"cross-scale":[56],"normalizing":[57],"flow":[58],"(CS-Flow)":[59],"enhanced":[61],"with":[62,84],"PCSENet":[63],"achieve":[65],"effective":[66],"at":[69],"image":[71],"level.":[72],"Specifically,":[73],"fully":[75],"network":[77],"original":[80,135,151],"method":[81,117,162],"replaced":[83],"This":[86],"substitution":[87],"reduces":[88],"network's":[90],"Flops":[91],"parameters":[93,144],"while":[94],"improving":[95],"model's":[97],"feature":[98],"extraction":[99],"capability.":[100],"We":[101],"conducted":[102],"experimental":[103],"analysis":[104],"utilizing":[105],"five":[106],"common":[107],"defects":[108],"from":[109],"InsPLAD":[111],"dataset.":[112],"Experiments":[113],"show":[114],"that":[115],"our":[116,138,161],"achieved":[118],"higher":[120],"AUROC":[121,128],"than":[122,149],"4":[124],"categories.":[125],"The":[126],"average":[127],"across":[129],"all":[130],"categories":[131],"also":[132],"surpassed":[133],"method.":[136],"Also,":[137],"has":[140],"approximately":[141],"52.74%":[142],"fewer":[143,147],"52.19%":[146],"FLOPs":[148],"one.":[152],"These":[153],"results":[154],"demonstrate":[155],"effectiveness":[157],"superiority":[159],"for":[163],"fault":[166],"detection.":[167]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
