Fine granularity vehicle multi-property recognition method based on convolutional neural network

Abstract

The invention relates to a fine granularity vehicle multi-property recognition method based on a convolutional neural network and belongs to the technical field of computer visual recognition. The method comprises the steps that a neural network structure is designed, including a convolution layer, a pooling layer and a full-connection layer, wherein the convolution layer and the pooling layer areresponsible for feature extraction, and a classification result is output by calculating an objective loss function on the last full-connection layer; a fine granularity vehicle dataset and a tag dataset are utilized to train the neural network, the training mode is supervised learning, and a stochastic gradient descent algorithm is utilized to adjust a weight matrix and offset; and a trained neural network model is used for performing vehicle property recognition. The method can be applied to multi-property recognition of a vehicle, the fine granularity vehicle dataset and the multi-propertytag dataset are utilized to obtain more abstract high-level expression of the vehicle through the convolutional neural network, invisible characteristics reflecting the nature of the to-be-recognizedvehicle are learnt from a large quantity of training samples, therefore, extensibility is higher, and recognition precision is higher.

Description

technical field [0001] The invention belongs to the technical field of computer vision recognition, and relates to a fine-grained vehicle multi-attribute recognition method based on a convolutional neural network. Background technique [0002] Along with economic development, automobiles have become the most important means of transportation for people, and the accompanying problem of urban traffic congestion is becoming more and more serious, and more and more "blocked cities" appear. Intelligent transportation system is considered to be the best solution to relieve traffic pressure at present, and as part of smart city and digital city, intelligent transportation system is mainly used in traffic flow monitoring, vehicle monitoring, highway toll station management, community intelligent management, parking lot management , traffic police law enforcement, public security criminal investigation, etc. Among them, vehicle detection and recognition is the most critical part of t...

AI Technical Summary

Problems solved by technology

However, these works are very preliminary to the original convolutional neural network architecture, and many important practical issues have not been discussed, especially involving vehicle multi-attribute recognition.

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