CNN Based Traffic Sign Recognition for Mini Autonomous Vehicles

Abstract. Advanced driving assistance systems (ADAS) could perform basic
object detection and classification to alert drivers for road conditions, vehicle
speed regulation, and etc. With the advances in the new hardware and software
platforms, deep learning has been used in ADAS technologies. Traffic signs are
an important part of road infrastructure. So, it is very important task to detect
and classify traffic signs for autonomous vehicles. In this paper, we firstly create
a traffic sign dataset from ZED stereo camera mounted on the top of Racecar
mini autonomous vehicle and we use Tiny-YOLO real-time object detection and
classification system to detect and classify traffic signs. Then, we test the model
on our dataset in terms of accuracy, loss, precision and intersection over union
performance metrics.


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