{"id":"https://openalex.org/W4416196010","doi":"https://doi.org/10.3390/info16110974","title":"DFA-YOLO: A Novel YOLO Model for Electric Power Operation Violation Recognition","display_name":"DFA-YOLO: A Novel YOLO Model for Electric Power Operation Violation Recognition","publication_year":2025,"publication_date":"2025-11-11","ids":{"openalex":"https://openalex.org/W4416196010","doi":"https://doi.org/10.3390/info16110974"},"language":"en","primary_location":{"id":"doi:10.3390/info16110974","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110974","pdf_url":"https://www.mdpi.com/2078-2489/16/11/974/pdf?version=1762855875","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/11/974/pdf?version=1762855875","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000359310","display_name":"Xiaoliang Qian","orcid":"https://orcid.org/0000-0002-4328-6411"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoliang Qian","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":"https://orcid.org/0000-0002-4328-6411","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117203089","display_name":"Xinyu Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Ding","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007909496","display_name":"Pengfei Wang","orcid":"https://orcid.org/0000-0001-9882-5059"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Wang","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102401005","display_name":"Jungang Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091712","display_name":"Zhengzhou University of Science and Technology","ror":"https://ror.org/00b3j7936","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210091712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jungang Guo","raw_affiliation_strings":["Zhengzhou Fengjia Technology Co., Ltd., Zhengzhou 450009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhengzhou Fengjia Technology Co., Ltd., Zhengzhou 450009, China","institution_ids":["https://openalex.org/I4210091712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113101584","display_name":"Hu Chen","orcid":"https://orcid.org/0000-0002-3925-998X"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Chen","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":"https://orcid.org/0000-0002-3925-998X","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100664990","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8770-3862"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Wang","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":"https://orcid.org/0000-0002-8770-3862","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111361295","display_name":"Peixu Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peixu Xing","raw_affiliation_strings":["College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China","institution_ids":["https://openalex.org/I23171815"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100664990","https://openalex.org/A5111361295"],"corresponding_institution_ids":["https://openalex.org/I23171815"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30917429,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"11","first_page":"974","last_page":"974"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7552000284194946,"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":0.7552000284194946,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.04050000011920929,"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/T13429","display_name":"Electricity Theft Detection Techniques","score":0.02370000071823597,"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/convolution","display_name":"Convolution (computer science)","score":0.657800018787384},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6132000088691711},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5927000045776367},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5800999999046326},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5580000281333923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5236999988555908},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.48750001192092896},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.48350000381469727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6815999746322632},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.657800018787384},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6132000088691711},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5927000045776367},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5800999999046326},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5580000281333923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5562999844551086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.48350000381469727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.36579999327659607},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.27570000290870667},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27320000529289246},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26829999685287476}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16110974","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110974","pdf_url":"https://www.mdpi.com/2078-2489/16/11/974/pdf?version=1762855875","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:637a77505ae347fabeee7ddc2d2bcf94","is_oa":true,"landing_page_url":"https://doaj.org/article/637a77505ae347fabeee7ddc2d2bcf94","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 11, p 974 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16110974","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110974","pdf_url":"https://www.mdpi.com/2078-2489/16/11/974/pdf?version=1762855875","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2298392526","display_name":null,"funder_award_id":"252300421063","funder_id":"https://openalex.org/F4320323845","funder_display_name":"Natural Science Foundation of Henan Province"},{"id":"https://openalex.org/G2850872778","display_name":null,"funder_award_id":"62076223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323845","display_name":"Natural Science Foundation of Henan Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4416196010.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,240],"You":[1],"Only":[2],"Look":[3],"Once":[4],"(YOLO)":[5],"series":[6],"of":[7,25,53,74,83,209,232,250,322],"models,":[8,302],"particularly":[9],"the":[10,42,51,81,89,152,182,218,224,229,235,244,248,251,264,320,323],"recently":[11],"introduced":[12,215],"YOLOv12":[13],"model,":[14,266],"have":[15,47],"demonstrated":[16],"significant":[17,269],"potential":[18],"in":[19,35,62,95,103,271,311],"achieving":[20],"accurate":[21],"and":[22,38,76,86,98,199,221,258,273,277,283,287,290,315],"rapid":[23],"recognition":[24],"electric":[26],"power":[27],"operation":[28],"violations,":[29],"due":[30],"to":[31,107,150,165,180,216,227,263],"their":[32,259],"comprehensive":[33],"advantages":[34],"detection":[36,64,90,128,211,313],"accuracy":[37,109],"real-time":[39,126,316],"inference.":[40],"However,":[41],"current":[43],"YOLO":[44,119,301],"models":[45],"still":[46],"three":[48,137],"limitations:":[49],"(1)":[50],"absence":[52],"a":[54,117,125,141,173,187,207],"dedicated":[55],"feature":[56,84,167,204,237],"extraction":[57,238],"for":[58,66,92,110,169],"multi-scale":[59,144,158,170],"objects,":[60],"resulting":[61],"suboptimal":[63],"capabilities":[65],"objects":[67,94],"with":[68,130,298],"varying":[69],"sizes;":[70],"(2)":[71],"naive":[72],"integration":[73],"spatial":[75],"channel":[77,200],"attentions,":[78],"which":[79,135,155,185],"restricts":[80],"enhancement":[82],"discriminability":[85],"consequently":[87],"impairs":[88],"performance":[91,310],"challenging":[93],"complex":[96],"backgrounds;":[97],"(3)":[99],"weak":[100],"representation":[101,168],"capability":[102],"low-level":[104,236],"features,":[105],"leading":[106],"insufficient":[108],"small-sized":[111],"objects.":[112,171],"To":[113],"address":[114,151,181,217],"these":[115],"limitations,":[116],"novel":[118],"model":[120,129],"named":[121],"DFA-YOLO":[122,267,307,324],"is":[123,148,178],"proposed,":[124],"object":[127],"YOLOv12n":[131],"as":[132],"its":[133],"baseline,":[134],"makes":[136],"key":[138],"contributions.":[139],"Firstly,":[140],"dynamic":[142],"weighted":[143,163],"convolution":[145,159],"(DWMConv)":[146],"module":[147,177],"proposed":[149,179,252],"first":[153],"limitation,":[154,184],"employs":[156],"lightweight":[157],"followed":[160],"by":[161,275,285,293],"learnable":[162],"fusion":[164],"enhance":[166],"Secondly,":[172],"full-dimensional":[174],"attention":[175,189,195],"(FDA)":[176],"second":[183],"gives":[186],"unified":[188],"computation":[190],"scheme":[191],"that":[192,306],"effectively":[193],"integrates":[194],"across":[196],"height,":[197],"width,":[198],"dimensions,":[201],"thereby":[202],"improving":[203],"discriminability.":[205],"Thirdly,":[206],"set":[208],"auxiliary":[210],"heads":[212],"(Aux-Heads)":[213],"are":[214],"third":[219],"limitation":[220],"inserted":[222],"into":[223],"backbone":[225],"network":[226],"strengthen":[228],"training":[230],"effect":[231],"labels":[233],"on":[234,243],"module.":[239],"ablation":[241],"studies":[242],"EPOVR-v1.0":[245],"dataset":[246],"demonstrate":[247],"validity":[249],"DWMConv":[253],"module,":[254,256],"FDA":[255],"Aux-Heads,":[257],"synergistic":[260],"integration.":[261],"Relative":[262],"baseline":[265],"achieves":[268,308],"improvements":[270],"mAP@0.5":[272],"mAP@0.5\u20130.95,":[274],"3.15%":[276],"4.13%,":[278],"respectively,":[279,289],"meanwhile":[280],"reducing":[281],"parameters":[282],"GFLOPS":[284],"0.06M":[286],"0.06,":[288],"increasing":[291],"FPS":[292],"3.52.":[294],"Comprehensive":[295],"quantitative":[296],"comparisons":[297],"nine":[299],"official":[300],"including":[303],"YOLOv13n,":[304],"confirm":[305],"superior":[309],"both":[312],"precision":[314],"inference,":[317],"further":[318],"validating":[319],"effectiveness":[321],"model.":[325]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-11-11T00:00:00"}