This paper establishes a multilevel dataset for solving the vehicle logo detection task; we call it ‘VLD-30’. Vehicle logo detection is applied to the Intelligent Transport System widely, such as vehicle monitoring. As for the object detection algorithm of deep-learning, a good dataset can improve the robustness of it. Our dataset has a very high reliability by including analysis on various factors. In order to confirm the dataset performance, we use the typical target detection algorithm, such as Faster-RCNN and YOLO. The experimental results show that our dataset achieves significant improvements for the small object detection, and vehicle logo detection is potential to be developed.
CITATION STYLE
Yang, S., Bo, C., Zhang, J., Wang, M., & Chen, L. (2020). A New Dataset for Vehicle Logo Detection. In Studies in Computational Intelligence (Vol. 810, pp. 171–177). Springer Verlag. https://doi.org/10.1007/978-3-030-04946-1_17
Mendeley helps you to discover research relevant for your work.