The Implications of Weather and Reflectivity Variations on Automatic Traffic Sign Recognition Performance
Automatic recognition of traffic signs in complex, real-world environments has become a pressing research concern with rapid improvements of smart technologies. Hence, this study leveraged an industry-grade object detection and classification algorithm (You-Only-Look-Once, YOLO) to develop an automa...
Saved in:
Main Authors: | Mudasser Seraj, Andres Rosales-Castellanos, Amr Shalkamy, Karim El-Basyouny, Tony Z. Qiu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/5513552 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand
by: Yuwei Bie, et al.
Published: (2018-01-01) -
Modeling Microscopic Car-Following Strategy of Mixed Traffic to Identify Optimal Platoon Configurations for Multiobjective Decision-Making
by: Mudasser Seraj, et al.
Published: (2018-01-01) -
Traffic Sign Recognition in Rainy Conditions Based on Federated Learning
by: Chen Yilin
Published: (2025-01-01) -
ResNet15: Weather Recognition on Traffic Road with Deep Convolutional Neural Network
by: Jingming Xia, et al.
Published: (2020-01-01) -
Effect of Signs Types on Level of Traffic Signs Understanding of Motorcyclists
by: Dewi Maulina, et al.
Published: (2023-07-01)