Aldo Calio'
Deep Learning-Based Real-Time Detection and Object Tracking on an Autonomous Rover with GPU based embedded device.
Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021
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Abstract
In recent years, there has been a growing interest in autonomous systems with artificial intelligence, especially in the military, home automation and smart cities sectors. In this project, the aim is to develop, through an artificial neural network capable of detecting objects, a system that can make a rover-type vehicle independent. An autonomous vehicle is a system capable of perceiving its environment and moving safely with little or no human input. Based on an appropriate network according to the needs, a tracking algorithm is developed, which gives the memory to the intelligence, i.e. it can assign an identity to any detected object, around frames in a real-time video.
The implementation of a tracking algorithm would allow the system to be more dynamic and to perform more complex functions than simply detecting and tracking the object frame by frame
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