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Federated Learning Method for Preserving Privacy in Face Recognition System
March 11, 2024, 4:45 a.m. | Enoch Solomon, Abraham Woubie
cs.CV updates on arXiv.org arxiv.org
Abstract: The state-of-the-art face recognition systems are typically trained on a single computer, utilizing extensive image datasets collected from various number of users. However, these datasets often contain sensitive personal information that users may hesitate to disclose. To address potential privacy concerns, we explore the application of federated learning, both with and without secure aggregators, in the context of both supervised and unsupervised face recognition systems. Federated learning facilitates the training of a shared model without …
abstract application art arxiv computer concerns cs.cv datasets explore face face recognition federated learning however image image datasets information personal information privacy recognition state systems type
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