Ivan Airola Sciot
Robustness and reliability of a 1D-ConvNet in trajectory prediction with data augmentation from capacitive sensors.
Rel. Luciano Lavagno, Mihai Teodor Lazarescu. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2022
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Abstract
Nowadays, Machine Learning is an expanding branch of artificial intelligence under computer science. Machine Learning consists in a system, called Neural Network (NN), which can learn something from given data. For this reason, Machine Learning has a wide range of uses, for example from agriculture to spacecrafts. In this thesis work it will be used to predict a trajectory of a person with the knowledge of data from capacitive sensors, which were used in past as proximity sensors and now they are flourishing on the Internet of Things technology, because they are cheaper than infrared sensors used to detect and track movements.
The goal of the thesis is to improve the robustness and reliability of a Neural Network in trajectory prediction, by adding noise to capacitive sensors data in Neural Network pre-process
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