Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...
Abstract: The rapid progress in sensor technology and computational capabilities has significantly improved real-time data collection, enabling precise monitoring of various phenomena and industrial ...
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