With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.
|Name||IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS|
|Conference||IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)|
|Period||20/03/20 → 22/03/20|