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Illegal hazardous chemical transport vehicle identification method and system based on convolutional neural network

A convolutional neural network and transportation vehicle technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as unrealizable, high labor costs, and long time-consuming, so as to reduce labor costs and consume less time , the effect of improving flexibility and portability

Active Publication Date: 2021-10-01
智广海联(天津)大数据技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If all roads are fully manually supervised, it will take a long time and the labor cost will be high, making it impossible to achieve

Method used

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  • Illegal hazardous chemical transport vehicle identification method and system based on convolutional neural network
  • Illegal hazardous chemical transport vehicle identification method and system based on convolutional neural network
  • Illegal hazardous chemical transport vehicle identification method and system based on convolutional neural network

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0077] refer to figure 1 , which is a convolutional neural network-based identification method for illegal hazardous chemicals transport vehicles disclosed in the present invention, comprising the following steps:

[0078] S100. Obtain training data, and then perform data standardization processing on the training data. The training data is an initial labeled image library, and the initial labeled image library includes labeled hazardous chemical pictures, hazardous chemical icons, and standard hazardous chemical transport vehicles. examples.

[0079] Wherein, step S100 further includes:

[0080] S110, image grayscale processing: Gaussian blur is performed on the image of the training data to reduce image noise, and then weighted grayscale processing is performed on the R, G, and B channels of the image. In this embodiment, the weights of R, G, and B are respectively selected 0.299, 0.587, 0.114.

[0081] S120. Image edge analysis: use the canny algorithm to detect edges in t...

Embodiment 2

[0120] refer to Figure 6 , an illegal hazardous chemicals vehicle identification system based on a convolutional neural network, comprising a first data input processing unit 401, a convolution operation unit 402, a second data input processing unit 403 and a decision output unit 404, wherein the convolution operation unit 402 It is connected to the first data input processing unit 401 , the second data input processing unit 403 is connected to the convolution operation unit 402 , and the decision output unit 404 is connected to the second data input processing unit 403 .

[0121] The first data input processing unit 401 is used for acquiring training data and performing standardization processing on the training data, where the training data is an initial labeled image library.

[0122] The convolution operation unit 402 includes a convolutional neural network calculation model, which is used to perform convolution operations on the processed training data, and obtain the fi...

Embodiment 3

[0127] refer to Figure 7 , is an embodiment of an electronic device provided in the present invention, and the electronic device includes: a processor 501 , and a memory 502 configured to store executable instructions of the processor 501 . Optionally, it may also include: a communication interface 503, configured to communicate with other devices.

[0128] Wherein, the processor 501 is configured to execute the method corresponding to the foregoing method embodiment by executing the executable instruction, and the specific implementation process may refer to the foregoing method embodiment, and details are not repeated here.

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PUM

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Abstract

The invention discloses an illegal hazardous chemical transport vehicle identification method based on a convolutional neural network, and the method comprises the following steps: S100, obtaining training data, and carrying out the data standardization processing; S200, performing convolution operation by using the convolutional neural network calculation model to obtain a trained calculation model and a final annotation image library; and S300, acquiring a local hazardous chemical vehicle database and to-be-identified data, calculating and identifying the to-be-identified data, comparing the to-be-identified data with the final annotation image library for judgment, outputting hazardous chemical vehicle characteristics or suspected hazardous chemical vehicle characteristics, then judging with the local hazardous chemical vehicle database, and distinguishing a standard hazardous chemical transport vehicle from an illegal hazardous chemical transport vehicle. The invention also discloses an illegal hazardous chemical substance transport vehicle identification system based on the convolutional neural network, the standard hazardous chemical substance transport vehicle and the illegal hazardous chemical substance transport vehicle in the traffic picture flow can be identified by using image identification and a convolutional neural network calculation model, the consumed time is less, and the labor cost is reduced.

Description

technical field [0001] The invention relates to the technical field of intelligent identification of hazardous chemical logistics, in particular to a method and system for identifying illegal hazardous chemical transport vehicles based on convolutional neural networks. Specifically, it belongs to G06Q10 / 08 in the IPC classification. Background technique [0002] With the rapid development of my country's economy, the volume of road and logistics transportation continues to increase, and traffic safety and smooth flow have become the top priority, especially the storage and logistics of hazardous chemicals. Due to its characteristics of flammability, explosion, poisoning, and pollution, accidents during transportation will cause huge losses. For the controlled transportation of hazardous chemicals, the coordinated operation of multiple departments is required, and real-time information exchange is required between these departments, and specific information should be display...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06T7/12G06T7/13G06T5/00G06T3/40G06N3/04G06N3/08
CPCG06T7/12G06T7/13G06T3/4007G06N3/084G06T2207/20081G06T2207/20084G06T2207/20192G06T2207/30248G06N3/045G06F18/214G06F18/24G06T5/90G06T5/70
Inventor 宫跃峰任衡王阳王璐
Owner 智广海联(天津)大数据技术有限公司