{"id":"https://openalex.org/W4416676946","doi":"https://doi.org/10.1109/dsaa65442.2025.11247996","title":"Hybrid Federated Learning Framework with Client - Tailored Attentive Feature Extractor for Agricultural Health Monitoring","display_name":"Hybrid Federated Learning Framework with Client - Tailored Attentive Feature Extractor for Agricultural Health Monitoring","publication_year":2025,"publication_date":"2025-10-09","ids":{"openalex":"https://openalex.org/W4416676946","doi":"https://doi.org/10.1109/dsaa65442.2025.11247996"},"language":null,"primary_location":{"id":"doi:10.1109/dsaa65442.2025.11247996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11247996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","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/A5009235815","display_name":"Antoni Jaszcz","orcid":"https://orcid.org/0000-0002-8997-0331"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Antoni Jaszcz","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116551731","display_name":"Agnieszka Polowczyk","orcid":null},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Agnieszka Polowczyk","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116551730","display_name":"Alicja Polowczyk","orcid":null},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Alicja Polowczyk","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107470500","display_name":"Katarzyna Wiltos","orcid":"https://orcid.org/0009-0001-6148-6257"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Katarzyna Wiltos","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048495064","display_name":"Dawid Po\u0142ap","orcid":"https://orcid.org/0000-0003-1972-5979"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Dawid Po\u0142ap","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016267473","display_name":"Marcin Wo\u017aniak","orcid":"https://orcid.org/0000-0002-9073-5347"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Marcin Wo\u017aniak","raw_affiliation_strings":["Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100"],"affiliations":[{"raw_affiliation_string":"Silesian University of Technology,Faculty of Applied Mathematics,Gliwice,Poland,44-100","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5009235815"],"corresponding_institution_ids":["https://openalex.org/I119004910"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27667228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10616","display_name":"Smart Agriculture and AI","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.957099974155426,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.006300000008195639,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.614799976348877},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5978999733924866},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5692999958992004},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5370000004768372},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4948999881744385},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4311999976634979},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.3970000147819519}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7294999957084656},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.614799976348877},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5978999733924866},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5370000004768372},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47200000286102295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4569000005722046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44699999690055847},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.33160001039505005},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.2712000012397766}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa65442.2025.11247996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa65442.2025.11247996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 12th International Conference on Data Science and Advanced Analytics (DSAA)","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":8,"referenced_works":["https://openalex.org/W2473156356","https://openalex.org/W2805764882","https://openalex.org/W4386716599","https://openalex.org/W4392406133","https://openalex.org/W4393973089","https://openalex.org/W4406320414","https://openalex.org/W4408229470","https://openalex.org/W4408412608"],"related_works":[],"abstract_inverted_index":{"Agricultural":[0],"health":[1],"monitoring":[2],"is":[3,30],"a":[4,46,55,63,69,79,106,112,118,124,198],"critical":[5],"task":[6],"in":[7,96,111,197],"ensuring":[8],"the":[9,135,138,149,154,158,165,178,181,191,202],"stability":[10],"of":[11,148,157,164,180,201,205],"modern":[12],"agriculture.":[13],"Many":[14],"plant":[15],"diseases":[16],"share":[17],"visual":[18],"similarities,":[19],"making":[20],"manual":[21],"inspection":[22],"both":[23,83],"time":[24],"consuming":[25],"and":[26,33,73,86,122,171],"error":[27],"prone,":[28],"which":[29],"why":[31],"robust":[32],"adaptable":[34],"disease":[35,127],"detection":[36],"frameworks":[37],"are":[38],"not":[39],"only":[40],"desirable":[41],"but":[42],"essential":[43],"to":[44,89],"maintaining":[45],"resilient":[47],"agricultural":[48],"ecosystem.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"propose":[54],"hybrid":[56,193],"federated":[57],"learning":[58],"(FL)":[59],"framework":[60,77,195],"that":[61],"integrates":[62],"globally":[64,84],"shared":[65,85],"feature":[66,146],"extractor":[67],"with":[68,82,190],"client-specific":[70],"self-attentive":[71],"branch":[72],"classifier.":[74],"The":[75,100,130,174],"proposed":[76,131,182,192],"uses":[78],"global":[80,139],"model":[81,159],"client-tailored":[87],"branches":[88],"achieve":[90],"better":[91,145],"performance":[92],"for":[93],"specialized":[94,155],"tasks":[95],"decentralized":[97],"training":[98,189],"scenarios.":[99],"experiments":[101],"were":[102],"carried":[103],"out":[104],"on":[105,161],"Plant":[107],"Village":[108],"data":[109],"set":[110],"scenario,":[113],"where":[114],"each":[115],"client":[116],"represented":[117],"different":[119,125],"crop":[120],"type":[121],"faced":[123],"leaf":[126,151,207],"classification":[128,200],"problem.":[129],"solution":[132],"revolved":[133],"around":[134],"clients":[136],"sharing":[137],"weights,":[140],"thus":[141],"simultaneously":[142],"contributing":[143],"towards":[144],"extraction":[147],"common":[150],"features,":[152],"while":[153],"segment":[156],"focused":[160],"proper":[162],"interpretation":[163],"extracted":[166],"features":[167],"(via":[168],"cross-attention":[169],"mechanism)":[170],"direct":[172],"classification.":[173],"results":[175],"obtained":[176],"demonstrate":[177],"effectiveness":[179],"approach":[183],"over":[184],"standard":[185],"local":[186],"training,":[187],"as":[188],"FL":[194],"resulted":[196],"perfect":[199],"precision":[203],"100%":[204],"apple":[206],"disease.":[208]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-25T00:00:00"}
