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1 Ergebnisse
1
FedAA: Using Non-sensitive Modalities to Improve Federated ..:
, In:
Proceedings of the 31st ACM International Conference on Multimedia
,
Chen, Dong
;
Tang, Siliang
;
Shen, Zijin
... - p. 3796-3806 , 2023
Link:
https://dl.acm.org/doi/10.1145/3581783.3611953
RT T1 <cTitle>Proceedings of the 31st ACM International Conference on Multimedia</cTitle>: T1 <Title>FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3611953&Exemplar=1&LAN=DE A1 Chen, Dong A1 Tang, Siliang A1 Shen, Zijin A1 Wang, Guoming A1 Xiao, Jun A1 Zhuang, Yueting A1 Yang, Carl PB ACM YR 2023 K1 adversarial learning K1 image privacy K1 non-iid K1 non-sensitive modality K1 sensitive modality K1 Computing methodologies K1 Artificial intelligence K1 Distributed artificial intelligence K1 Security and privacy K1 Human and societal aspects of security and privacy K1 Privacy protections SP 3796 OP 3806 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3581783.3611953 DO https://dl.acm.org/doi/10.1145/3581783.3611953 SF ELIB - SuUB Bremen
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