Journal of Chaohu University ›› 2018, Vol. 20 ›› Issue (6): 115-120.
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A vehicle classification model based on deep learning is proposed to deal with complex traffic scenes. The model consists of two parts: vehicle detection model and classification model. A region-based convolutional neural network （R-CNN）method is used in the vehicle detection model to extract a single vehicle image from a disorderly background image. This step provides data for the next classification model. In the vehicle classification model, an image of a vehicle is included into a CNN model and a feature is produced, and then a joint Bayesian network is used to implement the classification process. Experiments show that the method can effectively identify vehicle structures and models in traffic images.
