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Dangerous goods recognition system and method thereof

A dangerous goods and identification system technology, applied in the field of dangerous goods identification system, can solve problems such as lack of related solutions

Inactive Publication Date: 2017-12-15
SHENZHEN REEMAN INTELLIGENT EQUIP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because currently there is no mature artificial intelligence sales technology solution applied in business scenarios, and related solutions are missing, so related technical solutions will receive very high attention

Method used

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  • Dangerous goods recognition system and method thereof
  • Dangerous goods recognition system and method thereof
  • Dangerous goods recognition system and method thereof

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Embodiment Construction

[0056] In order to express the present invention more clearly, the present invention will be further described below in conjunction with the accompanying drawings.

[0057] refer to Figure 1-2 , a hazardous article identification system of the present invention, comprising an article identification server 1, an intelligent terminal 2 with a camera, and an alarm 3;

[0058] Item recognition server 1 includes:

[0059] The off-line training module 11 trains the marked item images and stores the features of related item images, designs a multi-layer network based on the CNN convolutional neural network algorithm, and uses the tensorflow framework to mark the marked item images, and obtains the best results through multiple practice analysis Optimal parameters, the forward propagation and backward propagation algorithms are executed through multiple rounds of iterations, and the gradient algorithm finds a relatively fast path, so that the difference between the learned feature v...

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Abstract

The invention discloses a dangerous goods recognition system and method thereof. According to the system, firstly, goods needing to be recognized is obtained through a camera on an intelligent terminal, and transmits image information to a goods recognition server, a server management module sends the image information to an inference module for image recognition, the inference module performs goods recognition on learned data through an offline training module, when it is read that the goods are dangerous, the inference module transmits the information to an alarm for risk prompts, and when it is read that the goods are not dangerous, the inference module transmits the information to the intelligent terminal for goods information display. The recognition scheme is offline learning, an offline training model is built, a user does not depend on the network, according to the requirement of the user, secondary development can be performed, the period is short, debugging and optimizing are performed according to the application scenarios, and the effect is better.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a dangerous article identification system and a method thereof. Background technique [0002] Artificial Intelligence (Artificial Intelligence), the English abbreviation is AI. It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a manner similar to human intelligence. Research in this field includes robotics, language recognition, image recognition, natural language processing and expert systems, etc. Since the birth of artificial intelligence, the theory and technology have become increasingly mature, and the application fields have also continued to expand. It can be imagined...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/10G06F18/24
Inventor 高子庆
Owner SHENZHEN REEMAN INTELLIGENT EQUIP CO LTD
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