{"id":"https://openalex.org/W3095274827","doi":"https://doi.org/10.1109/isc251055.2020.9239095","title":"Broken Power Strand Detection with Aerial Images: A Machine Learning based Approach","display_name":"Broken Power Strand Detection with Aerial Images: A Machine Learning based Approach","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3095274827","doi":"https://doi.org/10.1109/isc251055.2020.9239095","mag":"3095274827"},"language":"en","primary_location":{"id":"doi:10.1109/isc251055.2020.9239095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isc251055.2020.9239095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Smart Cities Conference (ISC2)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Broken_Power_Strand_Detection_with_Aerial_Images_A_Machine_Learning_based_Approach/27110635","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075076585","display_name":"Yifeng Pan","orcid":"https://orcid.org/0009-0003-6664-9531"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifeng Pan","raw_affiliation_strings":["Guangzhou Institute of Geography, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou, China","institution_ids":["https://openalex.org/I4210147158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453029","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0001-9178-4258"},"institutions":[{"id":"https://openalex.org/I8696757","display_name":"Singapore University of Social Sciences","ror":"https://ror.org/01s57k749","country_code":"SG","type":"education","lineage":["https://openalex.org/I8696757"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["Singapore University of Social Sciences, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Social Sciences, Singapore","institution_ids":["https://openalex.org/I8696757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001201547","display_name":"Ji Yang","orcid":"https://orcid.org/0000-0003-4092-2264"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Yang","raw_affiliation_strings":["Guangzhou Institute of Geography, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou, China","institution_ids":["https://openalex.org/I4210147158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101561578","display_name":"Zhang We","orcid":"https://orcid.org/0000-0001-6478-3110"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Singapore Institute of Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology, Singapore","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735407","display_name":"Yong Li","orcid":"https://orcid.org/0000-0003-2072-6012"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Guangzhou Institute of Geography, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou, China","institution_ids":["https://openalex.org/I4210147158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022822400","display_name":"Chun Sing Lai","orcid":"https://orcid.org/0000-0002-4169-4438"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chun Sing Lai","raw_affiliation_strings":["Brunel University London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Brunel University London, London, United Kingdom","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457086","display_name":"Xiaomei Wu","orcid":"https://orcid.org/0000-0002-4937-7680"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaomei Wu","raw_affiliation_strings":["Guangzhou Institute of Geography, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou, China","institution_ids":["https://openalex.org/I4210147158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029853791","display_name":"Loi Lei Lai","orcid":"https://orcid.org/0000-0003-4786-7931"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Loi Lei Lai","raw_affiliation_strings":["Guangzhou Institute of Geography, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou, China","institution_ids":["https://openalex.org/I4210147158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077598031","display_name":"Binzhuo Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I74872605","display_name":"China Southern Power Grid (China)","ror":"https://ror.org/03hkh9419","country_code":"CN","type":"company","lineage":["https://openalex.org/I74872605"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binzhuo Hong","raw_affiliation_strings":["Yangjiang Power Supply Bureau Guangdong Power Grid Co., Ltd, Yangjiang, China"],"affiliations":[{"raw_affiliation_string":"Yangjiang Power Supply Bureau Guangdong Power Grid Co., Ltd, Yangjiang, China","institution_ids":["https://openalex.org/I74872605"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5075076585"],"corresponding_institution_ids":["https://openalex.org/I4210147158"],"apc_list":null,"apc_paid":null,"fwci":0.8611,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.70887748,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13715","display_name":"Power Line Inspection Robots","score":0.9990000128746033,"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":0.9990000128746033,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9919000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.735551118850708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7059630155563354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6652498245239258},{"id":"https://openalex.org/keywords/electric-power-transmission","display_name":"Electric power transmission","score":0.6163789629936218},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.5525394678115845},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.503736674785614},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.49254950881004333},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4797059893608093},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44523507356643677},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4170122742652893},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3620310425758362},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34645602107048035},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15212643146514893},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11290082335472107}],"concepts":[{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.735551118850708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059630155563354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6652498245239258},{"id":"https://openalex.org/C140311924","wikidata":"https://www.wikidata.org/wiki/Q200928","display_name":"Electric power transmission","level":2,"score":0.6163789629936218},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.5525394678115845},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.503736674785614},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.49254950881004333},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4797059893608093},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44523507356643677},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4170122742652893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3620310425758362},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34645602107048035},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15212643146514893},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11290082335472107},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isc251055.2020.9239095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isc251055.2020.9239095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Smart Cities Conference (ISC2)","raw_type":"proceedings-article"},{"id":"pmh:oai:bura.brunel.ac.uk:2438/22026","is_oa":false,"landing_page_url":"http://bura.brunel.ac.uk/handle/2438/22026","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:figshare.com:article/27110635","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Broken_Power_Strand_Detection_with_Aerial_Images_A_Machine_Learning_based_Approach/27110635","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/27110635","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Broken_Power_Strand_Detection_with_Aerial_Images_A_Machine_Learning_based_Approach/27110635","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335357","display_name":"Guangdong Academy of Sciences","ror":"https://ror.org/01g9hkj35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1905153633","https://openalex.org/W1995865273","https://openalex.org/W2014430770","https://openalex.org/W2024626428","https://openalex.org/W2026390442","https://openalex.org/W2160815625","https://openalex.org/W2184045248","https://openalex.org/W2323086309","https://openalex.org/W2490023472","https://openalex.org/W2783876128","https://openalex.org/W2897772777","https://openalex.org/W2910009410","https://openalex.org/W2919115771","https://openalex.org/W2963100393","https://openalex.org/W6722680694","https://openalex.org/W6755607526"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W4206637278","https://openalex.org/W4386005305","https://openalex.org/W3082051559","https://openalex.org/W2781247653","https://openalex.org/W4386214543","https://openalex.org/W1969988626","https://openalex.org/W3173198409","https://openalex.org/W1682621979","https://openalex.org/W1571672972"],"abstract_inverted_index":{"Power":[0],"lines":[1,48],"are":[2,22,49,96,113,137],"essential":[3],"for":[4,51,141],"electricity":[5],"transmission":[6],"between":[7,85],"power":[8,19,28,47],"plant":[9],"and":[10,15,30,80,88,139],"consumption":[11],"point.":[12],"Periodical":[13],"inspection":[14],"assessment":[16],"of":[17,37,46,61,119,176],"the":[18,26,34,38,43,59,62,77,82,86,103,120,128,144,148,157,164,174,186,190],"line":[20],"damages":[21],"critical":[23],"to":[24,75,101,156],"ensure":[25],"uninterrupted":[27],"delivery":[29],"grid":[31],"stability.":[32],"With":[33],"recent":[35],"development":[36],"unmanned":[39],"aerial":[40,44,121],"vehicles":[41],"technology,":[42],"images":[45,142],"adopted":[50],"broken":[52,66,89],"strand":[53,67],"detection.":[54,105],"A":[55],"huge":[56],"challenge":[57],"is":[58,73,179],"lack":[60],"fatal":[63],"but":[64,189],"rare":[65],"images.":[68,122],"Thus,":[69],"an":[70],"oversampling":[71],"strategy":[72],"proposed":[74],"increase":[76],"data":[78,83,177,182,195],"diversity":[79],"reduce":[81],"imbalance":[84],"normal":[87],"lines.":[90],"In":[91],"addition,":[92],"image":[93,99],"background":[94],"noises":[95],"filtered":[97],"through":[98],"transformation":[100],"facilitate":[102],"anomaly":[104],"After":[106],"that,":[107],"five":[108],"popular":[109],"machine":[110],"learning":[111],"models":[112,129],"trained":[114,138],"on":[115],"four":[116],"representative":[117],"views":[118,159],"The":[123],"experiments":[124],"results":[125],"show":[126,168],"that":[127],"can":[130,150],"achieve":[131],"a":[132],"remarkable":[133,169],"performance":[134,191],"when":[135],"they":[136],"specialized":[140],"from":[143,153],"same":[145],"view.":[146],"Second,":[147],"model":[149],"be":[151],"generalized":[152],"one":[154],"view":[155],"other":[158],"sharing":[160],"similar":[161],"features,":[162],"where":[163],"neural":[165],"network":[166],"solutions":[167],"knowledge":[170],"transfer":[171],"capability.":[172],"Third,":[173],"impact":[175],"size":[178],"discussed.":[180],"More":[181],"does":[183],"help":[184],"promote":[185],"detection":[187],"accuracy,":[188],"gain":[192],"diminishes":[193],"in":[194],"size.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}