{"id":"https://openalex.org/W2990068936","doi":"https://doi.org/10.4018/ijaci.2020010102","title":"A Visual Detection Method for Foreign Objects in Power Lines Based on Mask R-CNN","display_name":"A Visual Detection Method for Foreign Objects in Power Lines Based on Mask R-CNN","publication_year":2019,"publication_date":"2019-11-25","ids":{"openalex":"https://openalex.org/W2990068936","doi":"https://doi.org/10.4018/ijaci.2020010102","mag":"2990068936"},"language":"en","primary_location":{"id":"doi:10.4018/ijaci.2020010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2020010102","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","raw_type":"journal-article"},"type":"article","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":"https://openalex.org/A5026744270","display_name":"Wenxiang Chen","orcid":"https://orcid.org/0000-0002-6183-6528"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenxiang Chen","raw_affiliation_strings":["Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073532127","display_name":"Yingna Li","orcid":"https://orcid.org/0009-0000-6721-8459"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingna Li","raw_affiliation_strings":["Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404426","display_name":"Chuan Li","orcid":"https://orcid.org/0000-0002-9985-8204"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Li","raw_affiliation_strings":["Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Application of Computer Technology of the Yunnan Province, KMUST, China","institution_ids":["https://openalex.org/I10660446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026744270"],"corresponding_institution_ids":["https://openalex.org/I10660446"],"apc_list":null,"apc_paid":null,"fwci":1.9391,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.89479572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"11","issue":"1","first_page":"34","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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":0.9980999827384949,"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/T13715","display_name":"Power Line Inspection Robots","score":0.9976000189781189,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9884999990463257,"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/computer-science","display_name":"Computer science","score":0.8892784118652344},{"id":"https://openalex.org/keywords/electric-power-transmission","display_name":"Electric power transmission","score":0.734830915927887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6914491057395935},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5980646014213562},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.584141194820404},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5788532495498657},{"id":"https://openalex.org/keywords/transmission-line","display_name":"Transmission line","score":0.528048574924469},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.48893609642982483},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44921353459358215},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4374810457229614},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3592304587364197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.349974125623703},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14983204007148743},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06489607691764832}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8892784118652344},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.734830915927887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6914491057395935},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5980646014213562},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.584141194820404},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5788532495498657},{"id":"https://openalex.org/C33441834","wikidata":"https://www.wikidata.org/wiki/Q693004","display_name":"Transmission line","level":2,"score":0.528048574924469},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.48893609642982483},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44921353459358215},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4374810457229614},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3592304587364197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.349974125623703},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14983204007148743},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06489607691764832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijaci.2020010102","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijaci.2020010102","pdf_url":null,"source":{"id":"https://openalex.org/S51041755","display_name":"International Journal of Ambient Computing and Intelligence","issn_l":"1941-6237","issn":["1941-6237","1941-6245"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Ambient Computing and Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jaci00:v:11:y:2020:i:1:p:34-47","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJACI.2020010102","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W1882819926","https://openalex.org/W1990109128","https://openalex.org/W2102605133","https://openalex.org/W2110798204","https://openalex.org/W2112796928","https://openalex.org/W2390072575","https://openalex.org/W2517325737","https://openalex.org/W2543402402","https://openalex.org/W2545357906","https://openalex.org/W2568243440","https://openalex.org/W2598405065","https://openalex.org/W2613718673","https://openalex.org/W2781188777","https://openalex.org/W2802292638","https://openalex.org/W2806070179","https://openalex.org/W2897593716","https://openalex.org/W2904480641","https://openalex.org/W2909074876","https://openalex.org/W2953106684","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963315052","https://openalex.org/W2964185410","https://openalex.org/W3103912303","https://openalex.org/W3106250896","https://openalex.org/W6676481782"],"related_works":["https://openalex.org/W3034732808","https://openalex.org/W4292830139","https://openalex.org/W3115307632","https://openalex.org/W939514953","https://openalex.org/W2949628984","https://openalex.org/W2289441543","https://openalex.org/W2773288753","https://openalex.org/W2388454303","https://openalex.org/W2096055231","https://openalex.org/W2144886705"],"abstract_inverted_index":{"The":[0,34,79],"high-voltage":[1],"power":[2],"lines":[3,126],"and":[4,14,43,46,105],"transmission":[5,32,77,125],"towers":[6],"are":[7,20,39],"large":[8,11],"in":[9,12,16,75,94,101],"volume,":[10],"number,":[13],"wide":[15],"coverage,":[17],"so":[18],"they":[19],"easily":[21],"attached":[22],"to":[23,41,127],"foreign":[24,73,109],"objects,":[25],"which":[26],"may":[27],"cause":[28],"failure":[29],"of":[30,49,108,124],"the":[31,47,66,76,86,91,102,113],"line.":[33],"existing":[35],"object":[36,110],"detection":[37,54,69,89],"methods":[38],"susceptible":[40],"weather":[42],"environmental":[44],"factors,":[45],"use":[48],"neural":[50],"networks":[51],"for":[52,71,121],"target":[53,88],"can":[55,118],"achieve":[56],"good":[57,99],"results.":[58],"Therefore,":[59],"this":[60,95],"article":[61,96],"uses":[62],"MASK":[63],"R-CNN":[64],"as":[65],"basic":[67],"network":[68],"method":[70,92],"detecting":[72],"objects":[74],"network.":[78],"experimental":[80],"results":[81,100],"show":[82],"that":[83],"compared":[84],"with":[85],"traditional":[87],"method,":[90],"adopted":[93],"has":[97],"achieved":[98],"speed,":[103],"efficiency,":[104],"recognition":[106,129],"precision":[107],"detection.":[111],"In":[112],"future,":[114],"image":[115],"processing":[116],"operations":[117],"be":[119],"performed":[120],"complex":[122],"backgrounds":[123],"improve":[128],"effect.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
