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Machine Learning algorithm evaluation on advanced driver assistance
Evaluación de algoritmos de Machine Learning para conducción



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Sun, Wenbo (2021) Machine Learning algorithm evaluation on advanced driver assistance. [Trabajo Fin de Grado]

Creative Commons Attribution Non-commercial.



In this research and development project, our main purpose is to study four deep learning architectures for real-time object detection of people and bicycles encountered in front of driving.
We use 4 different algorithms for the same data set, and compare the mAPs obtained after training. And discuss which method is the most accurate, but also consider the time it takes to get what is suitable for what kind of scene.
The project I came up with would like to be used in a driving assistance system. The system uses camera sensors to get input, and then uses algorithms to assist, so that the safety of the car is guaranteed when driving. At the same time, it can run on a lowperformance version of the machine and compare the fps of different algorithms.

Item Type:Trabajo Fin de Grado
Additional Information:

Trabajo de Fin de Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2020/2021.

García Sánchez, Carlos
Botella Juan, Guillermo
Uncontrolled Keywords:Computer vision, Autonomous driving, Convolutional neural network, Object detection, Deep learning, Machine learning, Feature selection and extraction, Driving assistance
Subjects:Sciences > Computer science
Título de Grado:Grado en Ingeniería Informática
ID Code:74574
Deposited On:19 Sep 2022 16:16
Last Modified:19 Sep 2022 16:16

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