A Real-Time Chinese Traffic Sign Detection Algorithm Based on Modified YOLOv2
Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traff...
Main Authors: | Jianming Zhang, Manting Huang, Xiaokang Jin, Xudong Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-11-01
|
Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/10/4/127 |
Similar Items
-
Real-Time Detection Method for Small Traffic Signs Based on Yolov3
by: Huibing Zhang, et al.
Published: (2020-01-01) -
Short Communication: Detecting Heavy Goods Vehicles in Rest Areas in Winter Conditions Using YOLOv5
by: Margrit Kasper-Eulaers, et al.
Published: (2021-03-01) -
An Improved Light-Weight Traffic Sign Recognition Algorithm Based on YOLOv4-Tiny
by: Lanmei Wang, et al.
Published: (2021-01-01) -
Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition
by: Gabriel Villalonga, et al.
Published: (2020-01-01) -
Traffic sign recognition based on synthesised training data
by: Chrysoulas, C., et al.
Published: (2018)