@mastersthesis{amslaurea16143,
title = {riconoscimento del guidatore attraverso la fotocamera frontale di uno smartphone},
author = {Giada Salvatori},
url = {https://amslaurea.unibo.it/id/eprint/16143},
year = {2018},
date = {2018-01-01},
abstract = {Nowadays car manufactures and others are investing more and more in the use of technologies in order to improve road safety. The purpose of this study is to succeed in creating a model, exploiting Machine Learning, in order to verify whether users, while they are operating their own smartphones, are driving or not, carrying out the identification through images obtainable by means of the front-facing camera of the device.
We intend to illustrate different types of checks on drivers and the reason why we have chosen to develop this theory; the techniques adopted and the problems encountered during its development, detailing, step by step, the project implementation and explaining the implementation decisions, providing also varations in the development and a demo for observing the results in an active way.},
keywords = {Driver detection, Image Recognition, Machine Learning, road safety, Smartphone, Tensor Flow},
pubstate = {published},
tppubtype = {mastersthesis}
}
Nowadays car manufactures and others are investing more and more in the use of technologies in order to improve road safety. The purpose of this study is to succeed in creating a model, exploiting Machine Learning, in order to verify whether users, while they are operating their own smartphones, are driving or not, carrying out the identification through images obtainable by means of the front-facing camera of the device.
We intend to illustrate different types of checks on drivers and the reason why we have chosen to develop this theory; the techniques adopted and the problems encountered during its development, detailing, step by step, the project implementation and explaining the implementation decisions, providing also varations in the development and a demo for observing the results in an active way.