| Title |
Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs |
| ID_Doc |
43751 |
| Authors |
Liu, YC; Reynolds, M; Huynh, D; Hassan, G |
| Title |
Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs |
| Year |
2020 |
| Published |
|
| DOI |
10.1109/icaiis49377.2020.9194930 |
| Abstract |
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. |
| Author Keywords |
Deep Learning; YOLOs; Image Processing; Vehicle Length Estimation |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000629437100023 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems |
| Research Area |
Computer Science |
| PDF |
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