Federated Learning for Assisting the Visually-Impaired Using Augmented Reality
This thesis investigates the creation and assessment of a Federated Learning (FL) system which improves real-time object recognition for visually-impaired applications through embedded AI and edge computing. The research divides into two distinct sections. The initial phase of the FL validation used a CNN trained on the MNIST dataset to allow controlled testing of model updates and communication b
