Abstract
Vehicle analysis is an important task in many intelligent applications, which involves vehicle-type classification(VTC), license-plate recognition(LPR) and vehicle make and model recognition(MMR). Among these tasks, MMR plays an important complementary role with respect to LPR. In this paper, we propose a novel framework to detect moving vehicle and MMR using convolutional neural networks. The frontal view of vehicle images first extracted and fed into convolutional neural networks for training and testing. The experimental results show that our proposed framework achieves favorable recognition accuracy 98.7% in terms of our vehicle MMR.
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