International Journal of Informatics and Communication Technology (IJ-ICT)
Vol 13, No 2: August 2024

Efficient traffic signal detection with tiny YOLOv4: enhancing road safety through computer vision

Santhiya, Santhiya (Unknown)
Johnraja Jebadurai, Immanuel (Unknown)
Leelipushpam Paulraj, Getzi Jeba (Unknown)
Veemaraj, Ebenezer (Unknown)
Sharance, Randlin Paul (Unknown)
Keren, Rubee (Unknown)
Karan, Kiruba (Unknown)



Article Info

Publish Date
01 Aug 2024

Abstract

As decades go by, technology advances and everything around us becomes smarter, such as televisions, mobile phones, robots, and so on. Artificial intelligence (AI) is applied in these technologies where AI assists the computer in making judgments like humans, and this intelligence is artificially fed to the model. The self-driving technique is a developing technology. Autonomous driving has been a broad and fast-expanding technology over the last decade. This model is carried out using the tiny you only look once (YOLO) algorithm. YOLO is mainly used for object detection classification. Tiny YOLO model is explored for the traffic signal detection. ROBI FLOW dataset is used for object detection which contains 2000+ image data to train the tiny YOLO model for traffic signal detection in real time. This model gives an improved accuracy and lightweight implementation compared to other models. Tiny YOLO is fast and accurate model for real-time traffic signal detection.

Copyrights © 2024






Journal Info

Abbrev

IJICT

Publisher

Subject

Computer Science & IT

Description

International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of ...