Improving Accuracy of Traffic Sign Detection Using Learning Method
Keita Kumagai, Tomio Goto · 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech) · 2022
In recent years, the demand for image recognition has been increasing. For example, face recognition can be used to unlock lock screens in smartphones, and it can also be combined with a temperature sensor to detect body temperature. It can also be applied to automatic driving, where it can recognize people, traffic lights, and signs using image recognition to increase safety. Automatic driving requires not only recognition but also object detection to estimate positions of objects at the same time. In addition, it is essential to improve the accuracy of detection to ensure safety. In this study, we focus on the detection of signs and try to improve the detection accuracy.