{"id":"https://openalex.org/W4396629984","doi":"https://doi.org/10.1145/3654446.3654511","title":"Research on Defect Detection of Insulators in Transmission Lines Based on Improved YOLOv5","display_name":"Research on Defect Detection of Insulators in Transmission Lines Based on Improved YOLOv5","publication_year":2023,"publication_date":"2023-12-08","ids":{"openalex":"https://openalex.org/W4396629984","doi":"https://doi.org/10.1145/3654446.3654511"},"language":"en","primary_location":{"id":"doi:10.1145/3654446.3654511","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3654446.3654511","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3654446.3654511","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3654446.3654511","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069293549","display_name":"H. Y. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156189","display_name":"Shanghai Dianji University","ror":"https://ror.org/055fene14","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haonan Li","raw_affiliation_strings":["Shanghai Dian Ji University, China"],"raw_orcid":"https://orcid.org/0009-0001-7730-0701","affiliations":[{"raw_affiliation_string":"Shanghai Dian Ji University, China","institution_ids":["https://openalex.org/I4210156189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086180037","display_name":"Wang Fang","orcid":"https://orcid.org/0009-0006-9346-1819"},"institutions":[{"id":"https://openalex.org/I4210156189","display_name":"Shanghai Dianji University","ror":"https://ror.org/055fene14","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Wang","raw_affiliation_strings":["Shanghai Dian Ji University, China"],"raw_orcid":"https://orcid.org/0009-0006-9346-1819","affiliations":[{"raw_affiliation_string":"Shanghai Dian Ji University, China","institution_ids":["https://openalex.org/I4210156189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210156189"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28354117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"361","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9943000078201294,"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/T11019","display_name":"Image Enhancement Techniques","score":0.986299991607666,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.967199981212616,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6887503862380981},{"id":"https://openalex.org/keywords/insulator","display_name":"Insulator (electricity)","score":0.5970128774642944},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49677807092666626},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48782971501350403},{"id":"https://openalex.org/keywords/electric-power-transmission","display_name":"Electric power transmission","score":0.4636368155479431},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4309624433517456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4268333911895752},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3424149751663208},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3202335238456726},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15768718719482422},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.07072192430496216}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887503862380981},{"id":"https://openalex.org/C212702","wikidata":"https://www.wikidata.org/wiki/Q178150","display_name":"Insulator (electricity)","level":2,"score":0.5970128774642944},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49677807092666626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48782971501350403},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.4636368155479431},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4309624433517456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4268333911895752},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3424149751663208},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3202335238456726},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15768718719482422},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.07072192430496216},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3654446.3654511","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3654446.3654511","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3654446.3654511","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3654446.3654511","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3654446.3654511","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3654446.3654511","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396629984.pdf","grobid_xml":"https://content.openalex.org/works/W4396629984.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W2912675002","https://openalex.org/W4226312434"],"related_works":["https://openalex.org/W2544488502","https://openalex.org/W2581053080","https://openalex.org/W2118169057","https://openalex.org/W1602302187","https://openalex.org/W4361853929","https://openalex.org/W2377969116","https://openalex.org/W2353564203","https://openalex.org/W4360995741","https://openalex.org/W4391185071","https://openalex.org/W2113932228"],"abstract_inverted_index":{"In":[0,63],"order":[1],"to":[2,35,47,81,93,103],"solve":[3],"the":[4,57,71,84,90,97,105,108,111,115,149,155,163,179],"problems":[5],"of":[6,39,56,86,110,135,139,144,181],"low":[7],"detection":[8,13,38,127,133,137,184],"accuracy":[9,134,143,150,165],"and":[10,19,52,113,141,162],"high":[11],"missed":[12],"rate":[14,157],"caused":[15],"by":[16,153,160,168],"complex":[17],"background":[18],"scale":[20,61],"changes":[21],"in":[22,25,178,185],"insulator":[23,66,182],"images":[24],"aerial":[26],"photography,":[27],"this":[28],"study":[29],"proposes":[30],"an":[31],"improved":[32,171],"YOLOv5-CMW":[33],"algorithm":[34],"achieve":[36,48,132],"accurate":[37],"target":[40,58],"insulators.":[41],"Firstly,":[42],"utilizing":[43],"cross":[44],"local":[45],"connectivity":[46],"multi-scale":[49,76],"feature":[50,54,78,87],"fusion":[51],"obtain":[53],"data":[55,119],"at":[59],"different":[60],"levels.":[62],"addition,":[64],"for":[65],"defects":[67],"with":[68,123,147],"smaller":[69],"targets,":[70],"backbone":[72],"network":[73],"combines":[74],"a":[75],"adaptive":[77],"attention":[79],"module":[80],"dynamically":[82],"adjust":[83],"importance":[85],"channels,":[88],"enhancing":[89],"model's":[91],"ability":[92],"represent":[94],"features.":[95],"Subsequently,":[96],"WIoU":[98],"loss":[99],"function":[100],"was":[101],"used":[102],"train":[104],"network,":[106],"improving":[107],"stability":[109],"model":[112,130],"accelerating":[114],"convergence":[116],"process.":[117],"Experimental":[118],"shows":[120],"that":[121],"compared":[122],"current":[124],"mainstream":[125],"single-level":[126],"algorithms,":[128],"our":[129],"can":[131],"94.2%,":[136],"integrity":[138],"93%,":[140],"average":[142,164],"94.9%.":[145],"Compared":[146],"YOLOv5s,":[148],"has":[151,158,166,173],"increased":[152,159,167],"3.0%,":[154],"recall":[156],"4.1%,":[161],"4.5%.":[169],"This":[170],"technology":[172],"shown":[174],"broad":[175],"application":[176],"potential":[177],"field":[180],"defect":[183],"power":[186],"systems.":[187]},"counts_by_year":[],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2025-10-10T00:00:00"}