📮 Federated Learning for Multimedia Data by Gautam Srivastava (.PDF)

Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for mission critical applications. Federated Learning (FL) is a Machine Learning (ML) technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized Machine Learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust Machine Learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data.

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