Classification of railway level crossing barrier and light signalling system using YOLOv3
Pavel Sikora, Martin Kiac, Malay Kishore Dutta
Abstract
Nowadays, the world is experiencing an increasing boom in deep learning. This is more and more used in many areas such as medicine, robotics, industry, security systems, etc. This article deals with the detection and classification of railway barriers at level crossings, railway warnings, and light signaling systems. The evaluation system uses cameras, which are suitably positioned to capture the entire scene at a given railway level crossing. The detection itself is done using image processing techniques and deep neural networks. The proposed system uses the GPU acceleration to achieve real-time capability.
Topics & Concepts
BoomComputer scienceArtificial intelligenceDeep learningLevel crossingRoboticsComputer visionDeep neural networksReal-time computingRobotEngineeringMechanical engineeringEnvironmental engineeringAutonomous Vehicle Technology and SafetyAdvanced Neural Network ApplicationsRemote Sensing and LiDAR Applications