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Violation snapshot image AI recognition system

A recognition system and image technology, applied in character and pattern recognition, instruments, biological neural network models, etc., can solve problems such as heavy workload and difficulty in accurate review, and achieve the effect of avoiding recognition congestion, facilitating recognition, and improving verification speed.

Pending Publication Date: 2021-08-06
哈尔滨鹏博普华科技发展有限责任公司
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  • Application Information

AI Technical Summary

Problems solved by technology

[0002] There are about 700,000 images of traffic checkpoints in a city every day, and it is planned to have about 1.4 million images of traffic checkpoints per day in the future. Currently, the images of traffic checkpoints are manually reviewed and then reported to the traffic cloud. Not only is the workload heavy, but it is also difficult to accurately review

Method used

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Examples

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Embodiment 1

[0025] see Figure 1-4 , the present invention provides the following technical solutions: an AI recognition system for snapping images against regulations, comprising an image input module 1 to be identified, an image preprocessing module 4 connected to the output of the image input module 1 to be identified, and an output end of the image preprocessing module 4 Connected with neural network model module 6, the input end of neural network model module 6 is connected with neural network model building module 5, and the output end of neural network model module 6 is connected with identification result output module 7;

[0026] The neural network model module 6 includes an image distribution module 61 and several neural network model recognition modules 62, the input end of the image distribution module 61 is connected with the image preprocessing module 4, and the output end of the image distribution module 61 is connected with several neural network model recognition modules. ...

Embodiment 2

[0035] The difference of this embodiment compared with embodiment 1 is:

[0036]Concrete, the output end of several neural network model identification modules 62 is connected with illegal image storehouse 2, and the input end and output end of image input module 1 to be identified are connected with image coincidence degree comparison module 3, and image coincidence degree contrast module 3 The input end and the output end are connected with the illegal image storage library 2, and the output end of the image coincidence degree comparison module 3 is connected with the identification result output module 7.

[0037] The working principle of this embodiment: before the identification by the neural network model module 6, the image to be recognized input module 1 inputs the image to be recognized into the image coincidence degree comparison module 3, and the image coincidence degree comparison module 3 compares the image to be recognized with the The images in the violation ima...

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Abstract

The invention discloses a violation snapshot image AI recognition system, which belongs to the technical field of artificial intelligence and comprises a to-be-recognized image input module, the output end of the to-be-recognized image input module is connected with an image preprocessing module, and the output end of the image preprocessing module is connected with a neural network model module. The input end of the neural network model module is connected with a neural network model establishment module, and the output end of the neural network model module is connected with an recognition result output module; the neural network model module comprises an image distribution module and a plurality of neural network model recognition modules; and the to-be-recognized image input module, the neural network model establishing module, the neural network model module and the recognition result output module are arranged, AI intelligent recognition of the violation image can be achieved through the neural network model, manual auditing is not needed, the workload of workers is relieved, and meanwhile the auditing precision is improved.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to an AI recognition system for capturing illegal images. Background technique [0002] There are about 700,000 images of traffic checkpoints in a city every day, and it is planned to have about 1.4 million images of traffic checkpoints per day in the future. Currently, the images of traffic checkpoints are manually reviewed and then reported to the traffic cloud. Not only is the workload heavy, but it is also difficult to accurately review . [0003] For this reason, it is necessary to design an AI recognition system for illegal snapshot images in order to solve the above-mentioned problems. Contents of the invention [0004] In order to solve the problems raised in the above-mentioned background technology. The invention provides an AI recognition system for snapping images against regulations, which has the characteristics of reducing the workload ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/40G06K9/62G06N3/08
CPCG06N3/08G06V20/54G06V10/30G06V10/267G06F18/214
Inventor 杨亚宁
Owner 哈尔滨鹏博普华科技发展有限责任公司
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