{"id":"https://openalex.org/W4393185339","doi":"https://doi.org/10.1145/3640115.3640178","title":"Application of UAV-Captured Image Inspection Based on Convolutional Neural Networks Tower Image Recognition and Defect Detection","display_name":"Application of UAV-Captured Image Inspection Based on Convolutional Neural Networks Tower Image Recognition and Defect Detection","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4393185339","doi":"https://doi.org/10.1145/3640115.3640178"},"language":"en","primary_location":{"id":"doi:10.1145/3640115.3640178","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3640115.3640178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Information Technologies and Electrical 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/A5028279707","display_name":"Yangyang Tian","orcid":"https://orcid.org/0000-0001-6283-5204"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yangyang Tian","raw_affiliation_strings":["State Grid Henan Electric Power Company Research Institute, China"],"raw_orcid":"https://orcid.org/0000-0001-6283-5204","affiliations":[{"raw_affiliation_string":"State Grid Henan Electric Power Company Research Institute, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065113467","display_name":"Q.B. Wang","orcid":"https://orcid.org/0009-0004-8420-1770"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["State Grid Henan Electric Power Company Research Institute, China"],"raw_orcid":"https://orcid.org/0009-0004-8420-1770","affiliations":[{"raw_affiliation_string":"State Grid Henan Electric Power Company Research Institute, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094248143","display_name":"Haiyan Zhi","orcid":"https://orcid.org/0009-0004-9860-014X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haiyan Zhi","raw_affiliation_strings":["State Grid Henan Electric Power Company Research Institute, China"],"raw_orcid":"https://orcid.org/0009-0004-9860-014X","affiliations":[{"raw_affiliation_string":"State Grid Henan Electric Power Company Research Institute, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085714428","display_name":"Ling Liu","orcid":"https://orcid.org/0009-0005-1526-8741"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ling Liu","raw_affiliation_strings":["Beijing Qianfang Innovation Technology Co., Ltd, China"],"raw_orcid":"https://orcid.org/0009-0005-1526-8741","affiliations":[{"raw_affiliation_string":"Beijing Qianfang Innovation Technology Co., Ltd, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114357364","display_name":"Bo Wang","orcid":"https://orcid.org/0009-0002-4124-1444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Beijing Qianfang Innovation Technology Co., Ltd, China"],"raw_orcid":"https://orcid.org/0009-0002-4124-1444","affiliations":[{"raw_affiliation_string":"Beijing Qianfang Innovation Technology Co., Ltd, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068215520","display_name":"Xiangyu Su","orcid":"https://orcid.org/0009-0007-0103-3479"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiangyu Su","raw_affiliation_strings":["Beijing Qianfang Innovation Technology Co., Ltd, China"],"raw_orcid":"https://orcid.org/0009-0007-0103-3479","affiliations":[{"raw_affiliation_string":"Beijing Qianfang Innovation Technology Co., Ltd, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"386","last_page":"390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9886999726295471,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9886999726295471,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.964900016784668,"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/T14158","display_name":"Optical Systems and Laser Technology","score":0.9348999857902527,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7890923023223877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7455812692642212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7215056419372559},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6015023589134216},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5302785634994507},{"id":"https://openalex.org/keywords/tower","display_name":"Tower","score":0.5111294388771057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4825719892978668},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4383200407028198},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4252017140388489},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15539124608039856}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7890923023223877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7455812692642212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7215056419372559},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6015023589134216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5302785634994507},{"id":"https://openalex.org/C2777831296","wikidata":"https://www.wikidata.org/wiki/Q12518","display_name":"Tower","level":2,"score":0.5111294388771057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4825719892978668},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4383200407028198},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4252017140388489},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15539124608039856},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3640115.3640178","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3640115.3640178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Information Technologies and Electrical Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W4313898268","https://openalex.org/W4386165120"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4214759293","https://openalex.org/W2948890638","https://openalex.org/W2377743247","https://openalex.org/W2481514411","https://openalex.org/W3213682227","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2367420223"],"abstract_inverted_index":{"UAV-captured":[0,33],"image":[1,21,34,46],"inspection":[2,16,35,45],"technology":[3,17],"has":[4,102],"been":[5],"widely":[6],"used":[7],"in":[8],"tower":[9,37,78,85],"recognition":[10,79,111],"and":[11,48,54,62,89,109],"defect":[12,94],"detection,":[13],"but":[14],"the":[15,56,65,83,87],"based":[18,31,38],"on":[19,32,39],"traditional":[20],"algorithms":[22],"is":[23,52,59,67],"relatively":[24],"efficient.":[25],"This":[26],"paper":[27],"proposes":[28],"an":[29],"algorithm":[30],"to":[36],"convolutional":[40],"neural":[41],"networks.":[42],"First,":[43],"on-site":[44],"training":[47],"test":[49],"data":[50,58,71],"set":[51,72],"established,":[53],"second,":[55],"original":[57],"reinforcement":[60],"processed":[61],"divided,":[63],"then":[64],"model":[66],"trained.":[68],"Finally,":[69],"actual":[70],"can":[73,80,96],"be":[74],"tested.":[75],"Accurate":[76],"of":[77,92],"realize":[81],"95%,":[82],"accurate":[84],"recognition,":[86],"accuracy":[88],"recall":[90],"rate":[91],"typical":[93],"detection":[95],"reach":[97],"more":[98],"than":[99],"80%.":[100],"It":[101],"better":[103],"identification":[104],"accuracy,":[105],"stronger":[106],"generalization":[107],"ability,":[108],"faster":[110],"speed.":[112]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
