Erich Malan
OPTIMIZATION OF CONVOLUTIONAL NEURAL NETWORKS TRAINING FOR FEDERATED LEARNING ON EMBEDDED SYSTEMS.
Rel. Andrea Calimera, Valentino Peluso. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2021
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Abstract
The advancement of low power technologies and the improvement of wireless communication systems and infrastructures, fueled the Internet of Things (IoT), enabling the proliferation of connected sensors able to collect and transmit data over the internet. Meanwhile, thanks to the recent breakthroughs in Artificial Intelligence (AI), Convolutional Neural Networks in particular, computers can learn trends from the collected data and extract meaningful insights to make decisions autonomously. IoT and AI are twin pillars of a new revolution: the Artificial Intelligence of Things (AIoT). This revolution poses several opportunities and challenges. The availability of large-scale datasets generated by pervasive networks of sensors enabled the development of AI models achieving unprecedented accuracy in many domains, e.g., computer vision and natural language understanding.
At the same time, the creation and management of centralized datasets are raising several privacy and security concerns
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