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A method, device, and equipment for vehicle identification based on convolutional neural network

A convolutional neural network and car model recognition technology, applied in the field of machine vision, can solve problems such as image segmentation process errors and affect the accuracy of recognition results, and achieve the effect of improving accuracy

Active Publication Date: 2020-11-17
ENNEW DIGITAL TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] However, when using the existing technology to identify car models, not only does it need to pre-train multiple convolutional neural networks, but also causes errors in the image segmentation process, which affects the accuracy of the recognition results

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  • A method, device, and equipment for vehicle identification based on convolutional neural network

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Embodiment Construction

[0030] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and corresponding drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0031] The car model identification method based on the convolutional neural network provided in the embodiment of this description, such as figure 1 As shown, it specifically includes the following parts:

[0032] Step S100, using the first number of convolutional layer units to extract local features of the vehicle image to be recognized.

[0033]...

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Abstract

The present application discloses a method, device and equipment for identifying a car model based on a convolutional neural network. Wherein, the vehicle type recognition method specifically includes, using a first number of convolutional layer units to extract local features of the vehicle image to be recognized; based on the local features, using a second number of convolutional layer units to extract global features of the vehicle image to be recognized ; According to the local feature and the global feature, and using the classification layer to identify the vehicle type of the vehicle in the vehicle image. In this application, the local features and global features extracted by the convolutional layer unit in the convolutional neural network are input to the classification layer, and the local features and global features of the vehicle image to be recognized can be taken into account in the identification of the vehicle type, avoiding the image features due to excessive Single, and the problem of losing feature detail information and resulting in a decrease in accuracy improves the accuracy of the recognition result.

Description

technical field [0001] The present application relates to the technical field of machine vision, and in particular to a method, device and equipment for vehicle identification based on convolutional neural network. Background technique [0002] With the construction of cities and the development of society, the number of vehicles on the streets is increasing, and the road conditions are becoming more and more complex. Traffic management is facing challenges in many aspects-vehicle congestion, traffic accidents, road obstacles, etc. It is far from enough to simply rely on the formulation of relevant regulations and manual monitoring by relevant departments, so a practical and effective solution is needed. Building an intelligent transportation system is an effective method, and it is also the trend of urban transportation development. [0003] The detection and identification of vehicles is the technical core of the intelligent transportation system. Vehicle identification p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06V2201/08G06N3/045G06F18/24
Inventor 陈安猛彭莉谯帅吴航
Owner ENNEW DIGITAL TECH CO LTD