One shot learning approach to identify drivers

Haddad, Malik, Sanders, David, Langner, Martin and Tewkesbury, Giles (2021) One shot learning approach to identify drivers. In: Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1.

Abstract

This paper presents a new approach to identify users of shared powered mobility platfroms using One Shot learning algorithm. An electronic circuit is created using a Raspberry Pi and a camera module. Python programming language is used to create a program to control the function of the camera module and conduct One Shot learning to identify users. A user interface containing Start and Stop buttons is created to operate the camera module. If Start is pressed, the Python program will trigger the camera to take a snapshot, then the program will identify the face in that snapshot and perform facial recognition to compare that face with a database of user facial images. If a match was found a message box popped-up showing the user name. Once a user is identified, their settings and preferences can be downloaded to the shared powered mobility platform. If the face in the snapshot did not match any of the user facial images in the data base, a message popped-up showing that user was not found in the database. Practical testing showed the system behaved satisfactorily and successfully detected users. One Shot learning allowed new users to be added to the database without the need to retrain the whole system.

Official URL:	https://doi.org/10.1007/978-3-030-82193-7_41
Item Type:	Conference or Workshop Item (Paper)
Disciplines:	Computing, Maths, Engineering and Natural Sciences > Computer Science Computing, Maths, Engineering and Natural Sciences > Data Science & AI
Depositing User:	Malik Haddad
Date Deposited:	21 Dec 2023 11:43
Last Modified:	10 Oct 2024 13:09
URI:	https://nul.repository.guildhe.ac.uk/id/eprint/1416

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