Convolutional neural network based vehicle logo identification method

The invention provides a convolutional neural network based vehicle logo identification method. The method is specifically implemented by the following steps of: (1) inputting a to-be-detected picture shot by a high-resolution camera device in a traffic intersection; (2) positioning a vehicle logo; (3) constructing and training a convolutional neural network; and (4) identifying the vehicle logo. With the adoption of the convolutional neural network (CNN) based vehicle logo identification method, the shortcomings of complicated extraction feature operator, poor timeliness and complicated model in the prior art can be effectively overcome, and the calculation amount is effectively reduced; and features of CNN self-learning have higher robustness on environmental change, so that the identification rate of the vehicle logo is increased.