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A Control Method for Passenger-vehicle Shunting Based on Convolutional Neural Network

A convolutional neural network and control method technology, applied in biological neural network models, neural architectures, instruments, etc., can solve the problem of low level of intelligence of the human-vehicle diversion method, and achieve better recognition effect, faster speed and intelligence high degree of effect

Active Publication Date: 2022-04-08
GUANGXI NORMAL UNIV
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AI Technical Summary

Problems solved by technology

[0003] What the present invention aims to solve is the problem that the intelligence degree of the existing people-vehicle shunting method is not high, and a kind of people-vehicle shunting control method based on convolutional neural network is provided

Method used

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  • A Control Method for Passenger-vehicle Shunting Based on Convolutional Neural Network
  • A Control Method for Passenger-vehicle Shunting Based on Convolutional Neural Network
  • A Control Method for Passenger-vehicle Shunting Based on Convolutional Neural Network

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Embodiment Construction

[0024] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific examples.

[0025] A control method for people-vehicle diversion based on convolutional neural network, such as figure 1 As shown, it specifically includes the following steps:

[0026] (1) Establish a target recognition model in the background control computer.

[0027] 1.1) Construct a convolutional neural network

[0028] In the convolutional neural network, the convolutional layer is composed of multiple feature maps, each feature map is composed of multiple neurons, and each neuron is convolved with the feature map of the previous layer through the convolution kernel. inferred. The convolution kernel is a weight matrix that covers what the network needs to learn, including weights and biases. The convolution operation here is different from the one-dimensional convolution op...

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Abstract

The invention discloses a method for controlling the diversion of people and vehicles based on a convolutional neural network. First, the convolutional neural network in the background control computer is trained and tested by using a training set and a test set to obtain a target recognition model, and then the target recognition model is used to collect real-time The image is used for target detection to complete the control of the flow of people and vehicles. The invention has the characteristics of high precision, fast detection speed, high intelligence, strong practicability and wide application range.

Description

technical field [0001] The invention relates to the technical field of convolutional neural networks, in particular to a control method for diverting traffic between people and vehicles based on convolutional neural networks. Background technique [0002] In places with dense flow of people and vehicles, it is often necessary to separate people and vehicles to ensure the safety of pedestrians. The existing pedestrian and vehicle diversion methods mostly use manual guarding and commanding to make the pedestrian passage only pass through pedestrians, but not vehicles, and at the same time make the vehicle passage only pass through vehicles, but not pedestrians, thus ensuring the safety of pedestrians and pedestrians. vehicle safety. However, this method requires guards to be on duty 24 hours a day, which is time-consuming and labor-intensive. Contents of the invention [0003] The purpose of the present invention is to solve the problem that the existing methods for divert...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/56G06V10/774G06V10/82G06K9/62G06N3/04
CPCG06V20/56G06N3/045G06F18/214
Inventor 魏书伟曾上游鲁健恒彭柯王新娇
Owner GUANGXI NORMAL UNIV
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