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Project

Middleware for Distributed Deep Learning Networks in Embedded Systems

Machine Learning and more in particular deep learning are gaining much more interest as a means to process and classify data. This is caused by growing experience in this domain, but also due to the availability of data. Indeed, many machine learning models greatly rely on data as the deep learning technologies need to undergo a training phase. Hence, the maturation of Internet of Things has led to a huge availability of data which, in its turn, boosted the adoption of deep learning across many application domains. This project aims at designing and developing a middleware framework to enhance the connectivity and information exchange of distributed deep learning architectures. We will investigate the ability to adapt to changing configurations and provide security measures to provide access control and secure data exchange between the distributed networks.
Date:26 Dec 2018 →  30 Sep 2020
Keywords:Deep learning network
Disciplines:Other information and computing sciences not elsewhere classified