2026-06-27T23:50:07Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/106042023-09-06T23:11:31Zcom_20.500.14352_1col_20.500.14352_8
Docta Complutense
advisor
García Sánchez, Carlos
advisor
Botella Juan, Guillermo
author
Sun, Wenbo
2023-06-17T10:57:14Z
2023-06-17T10:57:14Z
2021
https://hdl.handle.net/20.500.14352/10604
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.
eng
Atribución-NoComercial 3.0 España
Machine Learning algorithm evaluation on advanced driver assistance
bachelor thesis
URL
https://docta.ucm.es/bitstreams/d59b00fa-81e6-4244-a8a4-856f8207b80f/download
File
MD5
61f6c22609829d1e068791f26084e504
6062114
application/pdf
SUN 83701_WENBO_SUN_MACHINE_LEARNING_ALGORITHM_EVALUATION_ON_ADVANCED_DRIVER_ASSISTANCE_1006096_1675754450 (1).pdf
URL
https://docta.ucm.es/bitstreams/382b2da6-a013-41e1-aa5f-fd9118b3692f/download
File
MD5
f0edf21b36262dd2a74aba52be539771
67824
text/plain
SUN 83701_WENBO_SUN_MACHINE_LEARNING_ALGORITHM_EVALUATION_ON_ADVANCED_DRIVER_ASSISTANCE_1006096_1675754450 (1).pdf.txt