Lidia Fantauzzo
On the Challenges of Federated Learning in Semantic Segmentation across Domains.
Rel. Barbara Caputo, Debora Caldarola, Fabio Cermelli, Antonio Tavera. Politecnico di Torino, Master of science program in Mathematical Engineering, 2021
Abstract
Artificial Intelligence is the technology behind self-driving cars, and it has already walked in our lives in ways that many of us are unaware of. The necessity to protect clients' privacy becomes a concern as a result of this stealthy assault. Federated Learning is a machine learning setting with the goal of preserving data privacy and ensuring data security. This scenario involves training statistical models on remote devices such as self-driving cars while keeping data localized. A central server aggregates the parameters from each local training client using a predefined algorithm, without having direct access to their data, which can be sensitive such as car routes.
Following this, the updated global model is sent back to the client for iterative training
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