{"id":"https://openalex.org/W4410810563","doi":"https://doi.org/10.1109/rivf64335.2024.11009064","title":"Visual Explanations from Deep Networks Using GradCAM in Federated Learning","display_name":"Visual Explanations from Deep Networks Using GradCAM in Federated Learning","publication_year":2024,"publication_date":"2024-12-21","ids":{"openalex":"https://openalex.org/W4410810563","doi":"https://doi.org/10.1109/rivf64335.2024.11009064"},"language":"en","primary_location":{"id":"doi:10.1109/rivf64335.2024.11009064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf64335.2024.11009064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 RIVF International Conference on Computing and Communication Technologies (RIVF)","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/A5002312869","display_name":"Anh-Tu Tran","orcid":"https://orcid.org/0000-0002-8403-865X"},"institutions":[{"id":"https://openalex.org/I4210155035","display_name":"Academy of Cryptography Techniques","ror":"https://ror.org/05nfbnp91","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210155035"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Anh-Tu Tran","raw_affiliation_strings":["Academy of Cryptography Techniques"],"affiliations":[{"raw_affiliation_string":"Academy of Cryptography Techniques","institution_ids":["https://openalex.org/I4210155035"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113168376","display_name":"Trong-Nghia Mai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155035","display_name":"Academy of Cryptography Techniques","ror":"https://ror.org/05nfbnp91","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210155035"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Trong-Nghia Mai","raw_affiliation_strings":["Academy of Cryptography Techniques"],"affiliations":[{"raw_affiliation_string":"Academy of Cryptography Techniques","institution_ids":["https://openalex.org/I4210155035"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002473513","display_name":"Van-Quyet Nguyen","orcid":"https://orcid.org/0000-0002-6898-4224"},"institutions":[{"id":"https://openalex.org/I4210155035","display_name":"Academy of Cryptography Techniques","ror":"https://ror.org/05nfbnp91","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210155035"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van-Quyet Nguyen","raw_affiliation_strings":["Academy of Cryptography Techniques"],"affiliations":[{"raw_affiliation_string":"Academy of Cryptography Techniques","institution_ids":["https://openalex.org/I4210155035"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002312869"],"corresponding_institution_ids":["https://openalex.org/I4210155035"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71758526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"438","last_page":"443"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.90829998254776,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.90829998254776,"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":0.7154561877250671},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5625372529029846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46413013339042664},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.35500389337539673},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.321907639503479}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7154561877250671},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5625372529029846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46413013339042664},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.35500389337539673},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.321907639503479}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rivf64335.2024.11009064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rivf64335.2024.11009064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2516809705","https://openalex.org/W2934428127","https://openalex.org/W2962858109","https://openalex.org/W3175601496","https://openalex.org/W3199384803","https://openalex.org/W4214739326","https://openalex.org/W4310342251","https://openalex.org/W4362658902","https://openalex.org/W4366085876","https://openalex.org/W4385060316","https://openalex.org/W4385431427","https://openalex.org/W4386142022","https://openalex.org/W4386274177","https://openalex.org/W4391066287","https://openalex.org/W4391848979","https://openalex.org/W4399531961","https://openalex.org/W4400409820","https://openalex.org/W6728757088","https://openalex.org/W6729646992","https://openalex.org/W6737947904","https://openalex.org/W6846362436"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"In":[0],"the":[1,27,41,59,70,114,125,137],"realm":[2],"of":[3,29,43,72,104,116,129],"Explainable":[4],"Artificial":[5],"Intelligence":[6],"(XAI),":[7],"visual":[8,44,75,133],"explanations":[9,76],"play":[10],"a":[11,34,84],"crucial":[12],"role":[13],"in":[14],"demystifying":[15],"complex":[16],"models,":[17],"providing":[18],"insights":[19],"into":[20],"their":[21],"decision-making":[22],"processes.":[23],"This":[24,122],"paper":[25],"explores":[26],"integration":[28],"Federated":[30],"Learning":[31],"(FL)":[32],"as":[33,102,118],"method":[35],"to":[36,53],"enhance":[37],"privacy":[38,65],"without":[39],"compromising":[40],"quality":[42],"explanations.":[45],"FL,":[46],"by":[47,78,120],"design,":[48],"allows":[49],"multiple":[50],"decentralized":[51],"devices":[52],"collaboratively":[54],"train":[55],"models":[56,117],"while":[57,96],"keeping":[58],"data":[60,105],"localized,":[61],"thereby":[62],"significantly":[63],"mitigating":[64],"concerns.":[66],"We":[67],"specifically":[68],"evaluate":[69],"impact":[71],"FL":[73,97,131],"on":[74],"generated":[77],"Gradient-weighted":[79],"Class":[80],"Activation":[81],"Mapping":[82],"(Grad-CAM),":[83],"popular":[85],"technique":[86],"for":[87,139],"producing":[88],"class-discriminative":[89],"localization":[90],"maps.":[91],"Our":[92],"study":[93],"demonstrates":[94],"that":[95],"introduces":[98],"certain":[99],"challenges,":[100],"such":[101],"heterogeneity":[103],"across":[106],"different":[107],"devices,":[108],"it":[109],"does":[110],"not":[111],"substantially":[112],"degrade":[113],"interpretability":[115],"visualized":[119],"Grad-CAM.":[121],"research":[123],"highlights":[124],"feasibility":[126],"and":[127,142],"benefits":[128],"combining":[130],"with":[132],"explanation":[134],"techniques,":[135],"paving":[136],"way":[138],"more":[140],"secure":[141],"interpretable":[143],"AI":[144],"systems.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}