Vehicle type recognition method based on convolutional neural network

Abstract

The invention provides a vehicle type recognition method based on convolutional neural network. Based on a feature extraction module and a vehicle type recognition module, the vehicle type recognition method comprises the following steps: establishing a neural network for vehicle type recognition by designing a convoluting and pooling layer, a full connection layer and a classifier, wherein the convoluting and pooling layer and the full connection layer are used for extracting vehicle type features, and the classifier is used for performing classified vehicle type recognition; training the neural network by using a database containing different vehicle type features; the training way is that labeled data are learned in a supervised manner, and regulating weighting parameter matrixes and offsets by a stochastic gradient descent method; obtaining the well-trained weighting parameter matrixes and offsets in layers, correspondingly assigning the weighting parameter matrixes and the offsets to the layers in the neural network, wherein the neural network has the functions of extracting and recognizing the vehicle type features. By the vehicle type recognition method, the convolutional neural network and the vehicle type recognition are creatively combined; different from the conventional vehicle type recognition method, by the vehicle type recognition method provided by the invention, the accuracy of the vehicle type recognition can be obviously improved.

Description

Technical field [0001] The present invention relates to the field of Internet of Things, in particular to a method for vehicle identification based on convolutional neural network Background technique [0002] Convolutional neural network is a kind of artificial neural network, which has become a research hotspot in the field of image recognition and speech analysis. The technologies closest to the present invention are: [0003] (1) The paper "Research on Convolutional Neural Networks and Its Application in License Plate Recognition System", which introduces the concept and development of convolutional neural networks, and uses convolutional neural networks to recognize preprocessed license plates. In order to achieve a relatively satisfactory recognition rate, some other papers have also applied artificial neural networks to the recognition of license plates; [0004] (2) In the paper "Research on Video-Based Vehicle Model Recognition", the SURF feature extraction method is used ...

AI Technical Summary

Problems solved by technology

However, the research represented by "Research on Vehicle Model Recognition Based on Video" is based on the traditional artificial feature extraction method, which has relatively large limitations and does not have the ability of machine self-learning

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