M. Saad Alam
- Student, Department of Electrical Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
- Phd Scholar, Department of Electrical Engineering, Zakir Husain College of Engineering and Technology, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
In this work, we compare the detection accuracy and speed of several state of the art models for the task of detecting red and green traffic lights. We compare detection performance and speed of YOLOv4, ScaledYOLOv4 and YOLOR. All of these are single stage object detection models. Two stage models have good detection accuracy but are slower than single stage detectors, single stage detectors are faster and also have good detection accuracy which makes them reliable in real time object detection. We discuss about the object detection models and the evaluation metric that we used to score our models. Than we discuss about the results of our work.
Keywords: Object Detection, Self Driving Cars, Deep Learning, Traffic, Light Detection
[This article belongs to International Journal of Analog Integrated Circuits(ijaic)]
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|Received||June 16, 2022|
|Accepted||June 23, 2022|
|Published||July 7, 2022|