{"id":"https://openalex.org/W2939388529","doi":"https://doi.org/10.1145/3313991.3314005","title":"An Improved Faster R-CNN Algorithm for Electric Equipment Detection","display_name":"An Improved Faster R-CNN Algorithm for Electric Equipment Detection","publication_year":2019,"publication_date":"2019-02-23","ids":{"openalex":"https://openalex.org/W2939388529","doi":"https://doi.org/10.1145/3313991.3314005","mag":"2939388529"},"language":"en","primary_location":{"id":"doi:10.1145/3313991.3314005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313991.3314005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Computer and Automation Engineering","raw_type":"proceedings-article"},"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":"https://openalex.org/A5100705672","display_name":"Jianlong Guo","orcid":"https://orcid.org/0000-0001-9208-4341"},"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":"Guo Jianlong","raw_affiliation_strings":["Guangdong Power Grid, Guangzhou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Power Grid, Guangzhou, Guangdong","institution_ids":["https://openalex.org/I74872605"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102938536","display_name":"Weixia Feng","orcid":"https://orcid.org/0000-0001-6260-4131"},"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":"Feng Weixia","raw_affiliation_strings":["Guangdong Power Grid, Guangzhou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Power Grid, Guangzhou, Guangdong","institution_ids":["https://openalex.org/I74872605"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091901485","display_name":"Manhua Wen","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":"Wen Manhua","raw_affiliation_strings":["Guangdong Power Grid, Guangzhou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Power Grid, Guangzhou, Guangdong","institution_ids":["https://openalex.org/I74872605"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74872605"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9876000285148621,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9498000144958496,"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/computer-science","display_name":"Computer science","score":0.7815726399421692},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6389802694320679},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6192513704299927},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5559791326522827},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43783101439476013},{"id":"https://openalex.org/keywords/insulator","display_name":"Insulator (electricity)","score":0.42657583951950073},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.14634069800376892},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.13996216654777527},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12716397643089294}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7815726399421692},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6389802694320679},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6192513704299927},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5559791326522827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43783101439476013},{"id":"https://openalex.org/C212702","wikidata":"https://www.wikidata.org/wiki/Q178150","display_name":"Insulator (electricity)","level":2,"score":0.42657583951950073},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.14634069800376892},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.13996216654777527},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12716397643089294},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3313991.3314005","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3313991.3314005","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Computer and Automation Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1849277567","https://openalex.org/W2920704738","https://openalex.org/W2953106684"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2544423928","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2140798747","https://openalex.org/W2052122378","https://openalex.org/W2948169060"],"abstract_inverted_index":{"More":[0],"and":[1,4,43,69,100,121],"more":[2,55],"images":[3],"videos":[5],"have":[6],"been":[7],"collected":[8],"in":[9,23],"power":[10,101],"system,":[11],"however,":[12],"it":[13],"is":[14,112,118],"still":[15],"a":[16],"challenge":[17],"to":[18,34,41,67,77,86],"recognize":[19,44,70],"the":[20,24,45,49,59,63,71,79,88,103,109,127],"electric":[21,46,50,72],"equipment":[22,47,51,73],"unstructured":[25],"multimedia":[26],"stream":[27],"automatically.":[28],"In":[29,75],"this":[30],"paper,":[31],"we":[32,57,82],"propose":[33,83],"apply":[35],"an":[36],"improved":[37],"Faster":[38,64,129],"R-CNN":[39,65,130],"algorithm":[40,85,111],"detect":[42,68],"for":[48,97],"images.":[52],"To":[53],"be":[54],"specific,":[56],"adjust":[58],"key":[60],"parameters":[61],"of":[62,108,126],"framework":[66],"simultaneously.":[74],"order":[76],"improve":[78],"recognition":[80,105],"accuracy,":[81],"DisturbIoU":[84],"prevent":[87],"network":[89],"training":[90],"from":[91],"over-fitting.":[92],"Experiment":[93],"results":[94],"show":[95],"that":[96,125],"insulator,":[98],"transformer":[99],"pole,":[102],"average":[104],"accuracy":[106],"rate":[107],"proposed":[110],"96.33%,":[113],"99.89%,":[114],"97.98%":[115],"respectively,":[116],"which":[117],"3.28%,":[119],"6.02%":[120],"6.21%":[122],"higher":[123],"than":[124],"traditional":[128],"algorithm.":[131]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}