A New Dataset for Vehicle Logo Detection
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.
KeywordsVLD-30 Deep-learning Vehicle logo detection
This work is supported by Key Research Guidance Plan Project of Liaoning Province (No. 2017104013), Natural Science Foundation of Liaoning Province (No. 201700133).
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