Traffic sign detection in unconstrained environment using improved YOLOv4-Reference-Cited by-同舟云学术

Traffic sign detection in unconstrained environment using improved YOLOv4

Author:

Saxena Swastik^ORCID,Dey Somnath^ORCID,Shah Miten,Gupta Sundesh

Funder

Department of Computer Science and Engineering, Seoul National University

Ministry of Higher Education, Malaysia

Indian Institute of Technology Indore

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. Real-time speed sign detection using the radial symmetry detector;Barnes;IEEE Transactions on Intelligent Transportation Systems,2008

2. An improved traffic signs recognition and tracking method for driver assistance system;Ben Romdhane,2016

3. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

4. The mapillary traffic sign dataset for detection and classification on a global scale;Ertler,2020

5. Fast R-CNN;Girshick,2015

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