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Vehicle re-identification system for road side unit application

Vehicle re-identification is one of the complex smart traffic issues, due to the large intra-class variation and high interclass similarity, it is hard to be solved through traditional hand-crafted features. In this paper, we proposed a vehicle re-identification system based on deep learning techniques, which is able to re-identify the vehicles through deep features under acceptable operation time on Nvidia Jetson TX2. We have collected multiple sequences captured from real-world road side units (RSU) for system evaluation experiments, and the results indicate that it is highly possible to be adopted for real world traffic applications.