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Station caption detection method, device and readable storage medium

A detection method and technology of station logo, applied in the field of artificial intelligence, can solve the problems of high difficulty and cost of detection, large workload of labeling, and sparse amount of data.

Inactive Publication Date: 2019-12-24
NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] There are many types of existing data but the amount of data is scarce, and the workload of manual pre-labeling is heavy, and it is difficult and costly to use conventional target detection

Method used

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  • Station caption detection method, device and readable storage medium
  • Station caption detection method, device and readable storage medium
  • Station caption detection method, device and readable storage medium

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Embodiment Construction

[0043] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0044] The first embodiment of the present invention proposes the first aspect. The first embodiment of the present invention proposes a station logo detection method, such as figure 1 As shown, the method includes the following steps:

[0045] Obtaining a station logo data set, and grouping the station logo data set to obtain a station logo training set;

[0046] Constructing a multi-loss fused twin neural network, and training t...

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Abstract

The invention discloses a station caption detection method, a station caption detection device and a readable storage medium. The method comprises the following steps: obtaining a station caption dataset, and grouping the station caption data set to obtain a station caption training set; constructing a multi-loss fusion twin neural network, and training the constructed multi-loss fusion twin neural network based on the station caption training set to obtain a trained multi-loss fusion twin neural network; and detecting a station caption to be detected through the trained multi-loss fused twinneural network. According to the method, a twin neural network framework is constructed, so that the influence of insufficient samples on a training network is well eliminated. The unknown new typesof sensitive station captions can be better detected.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a station logo detection method, device and readable storage medium. Background technique [0002] With the development of science and technology and the change of information carriers, all kinds of information gather together. Today, when the Internet is integrated into every corner of society, Internet empowerment gives people more voices, and also gives some people who spread bad information an opportunity to take advantage of it. . The Internet affects the vast number of netizens in terms of information dissemination and public opinion guidance, so maintaining network information security has become a top priority. [0003] There are many types of existing data but the amount of data is scarce, and the workload of manual pre-labeling is heavy. It is difficult and costly to use conventional target detection. Contents of the invention [0004] Embodiments of...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62G06K9/00
CPCG06N3/08G06V20/40G06N3/045G06F18/22G06F18/2415G06F18/214
Inventor 段运强井雅琪李扬曦刘雨帆张翠任博雅时磊胡燕林郭承禹佟玲玲段东圣张迎雪原春锋李兵
Owner NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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