{"id":"https://openalex.org/W4388482969","doi":"https://doi.org/10.1109/fmec59375.2023.10305958","title":"Federated Ensemble YOLOv5 \u2013 A Better Generalized Object Detection Algorithm","display_name":"Federated Ensemble YOLOv5 \u2013 A Better Generalized Object Detection Algorithm","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4388482969","doi":"https://doi.org/10.1109/fmec59375.2023.10305958"},"language":"en","primary_location":{"id":"doi:10.1109/fmec59375.2023.10305958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fmec59375.2023.10305958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC)","raw_type":"proceedings-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/A5051490561","display_name":"Vinit Hegiste","orcid":"https://orcid.org/0000-0001-6944-1988"},"institutions":[{"id":"https://openalex.org/I4387152675","display_name":"Rheinland-Pf\u00e4lzische Technische Universit\u00e4t Kaiserslautern-Landau","ror":"https://ror.org/01qrts582","country_code":null,"type":"education","lineage":["https://openalex.org/I4387152675"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Vinit Hegiste","raw_affiliation_strings":["Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau,Kaiserslautern,Germany","Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I4387152675"]},{"raw_affiliation_string":"Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I4387152675"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058225688","display_name":"Tatjana Legler","orcid":"https://orcid.org/0000-0002-7297-0845"},"institutions":[{"id":"https://openalex.org/I4387152675","display_name":"Rheinland-Pf\u00e4lzische Technische Universit\u00e4t Kaiserslautern-Landau","ror":"https://ror.org/01qrts582","country_code":null,"type":"education","lineage":["https://openalex.org/I4387152675"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tatjana Legler","raw_affiliation_strings":["Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau,Kaiserslautern,Germany","Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau, Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I4387152675"]},{"raw_affiliation_string":"Chair of Machine Tools and Control Systems, RPTU Kaiserslautern-Landau, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I4387152675"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031150780","display_name":"Martin Ruskowski","orcid":"https://orcid.org/0000-0002-6534-9057"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Ruskowski","raw_affiliation_strings":["Innovative Factory Systems (IFS), German Research Center for Artificial Intelligence (DFKI),Kaiserslautern,Germany","Innovative Factory Systems (IFS), German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany"],"affiliations":[{"raw_affiliation_string":"Innovative Factory Systems (IFS), German Research Center for Artificial Intelligence (DFKI),Kaiserslautern,Germany","institution_ids":["https://openalex.org/I33256026"]},{"raw_affiliation_string":"Innovative Factory Systems (IFS), German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051490561"],"corresponding_institution_ids":["https://openalex.org/I4387152675"],"apc_list":null,"apc_paid":null,"fwci":1.7483,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.87887647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9664000272750854,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9157000184059143,"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":0.8163625001907349},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7621252536773682},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6463416218757629},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6457761526107788},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6377019882202148},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6193943619728088},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6111177206039429},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.5776665806770325},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5666584372520447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5154603123664856},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4106025695800781},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2530103921890259},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16312554478645325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08302298188209534}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8163625001907349},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7621252536773682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6463416218757629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6457761526107788},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6377019882202148},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6193943619728088},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6111177206039429},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.5776665806770325},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5666584372520447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5154603123664856},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4106025695800781},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2530103921890259},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16312554478645325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08302298188209534},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fmec59375.2023.10305958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fmec59375.2023.10305958","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC)","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":17,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1977405994","https://openalex.org/W2029950324","https://openalex.org/W2084362125","https://openalex.org/W2963037989","https://openalex.org/W2970602317","https://openalex.org/W3004732066","https://openalex.org/W3035046187","https://openalex.org/W3130806609","https://openalex.org/W3210311771","https://openalex.org/W4232478844","https://openalex.org/W4312588485","https://openalex.org/W4318619660","https://openalex.org/W4379536814","https://openalex.org/W4388483222","https://openalex.org/W6728757088","https://openalex.org/W6779308105"],"related_works":["https://openalex.org/W3036286480","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Federated":[0,20,24],"learning":[1,17,30,201],"(FL)":[2],"has":[3,32],"gained":[4],"significant":[5],"traction":[6],"as":[7,52,183,191],"a":[8,53,64,79,90,100,137,166,175,184,192,199],"privacy-preserving":[9],"algorithm,":[10],"but":[11,189],"the":[12,45,76,103,114,118,133,148,196],"underlying":[13],"resemblances":[14],"of":[15,39,47,78,102,117,139,169,198],"federated":[16],"algorithms":[18,31],"like":[19],"averaging":[21],"(FedAvg)":[22],"or":[23],"SGD":[25],"(Fed":[26],"SGD)":[27],"to":[28,43,49,55,59,165,186,194],"ensemble":[29,161],"not":[33,145,181],"been":[34],"fully":[35],"explored.":[36],"The":[37],"purpose":[38],"this":[40],"paper":[41],"is":[42],"examine":[44],"application":[46],"FL":[48,84,119,155,177],"object":[50,70,120],"detection":[51,71],"method":[54,185,193],"enhance":[56,187,195],"generalizability,":[57],"and":[58,88,171],"compare":[60],"its":[61],"performance":[62,77,197],"against":[63],"centralized":[65,108],"training":[66,149],"approach":[67],"for":[68,107,129],"an":[69,160],"algorithm.":[72],"Specifically,":[73],"we":[74],"investigate":[75],"YOLOv5":[80],"model":[81,123],"trained":[82],"using":[83],"across":[85],"multiple":[86],"clients":[87,144],"employ":[89],"random":[91],"sampling":[92],"strategy":[93],"without":[94],"replacement,":[95],"so":[96],"each":[97],"client":[98],"holds":[99],"portion":[101],"same":[104],"dataset":[105],"used":[106],"training.":[109],"Our":[110],"experimental":[111],"results":[112],"showcase":[113],"superior":[115],"efficiency":[116],"detector's":[121],"global":[122],"in":[124,147],"generating":[125],"accurate":[126],"bounding":[127],"boxes":[128],"unseen":[130],"objects,":[131],"with":[132],"test":[134],"set":[135],"being":[136],"mixture":[138],"objects":[140],"from":[141,159],"two":[142],"distinct":[143],"represented":[146],"dataset.":[150],"These":[151],"findings":[152],"suggest":[153],"that":[154],"can":[156,178],"be":[157,179],"viewed":[158],"algorithm":[162],"perspective,":[163],"akin":[164],"synergistic":[167],"blend":[168],"Bagging":[170],"Boosting":[172],"techniques.":[173],"As":[174],"result,":[176],"seen":[180],"only":[182],"privacy,":[188],"also":[190],"machine":[200],"model.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}