Road traffic target attribute identification method based on deep convolutional neural network

The invention belongs to the technical field of application of artificial intelligence, big data and convolutional neural networks in traffic, and particularly relates to a road traffic target attribute recognition method based on a deep convolutional neural network. A first sub-server, a second sub-server, a third sub-server and a fourth sub-server are built on the basis of the total server; a total database is established, the combination of numbers, letters and underlines is used as the name of the total data, and the name of the database is different from the names of other databases, that is, it is guaranteed that the name of the total data is unique; the system has the advantages that whether the license plate of the vehicle is normal, whether the annual inspection mark is pasted and whether the vehicle owner illegally modifies the vehicle are known, so that the condition of the vehicle is comprehensively known, the task load of the traffic bureau is greatly reduced, the corresponding sub-server is arra