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Labeling model training method and device

A technology for labeling models and training methods, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as manpower consumption, low efficiency, manual labeling errors, etc., and achieve the effect of improving labeling accuracy

Pending Publication Date: 2020-01-03
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the quality inspection scenario, the amount of image data is very large, relying on the annotation operation of the annotator will consume a lot of manpower and the efficiency is very low
At the same time, there is a high possibility of errors in manual labeling

Method used

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  • Labeling model training method and device
  • Labeling model training method and device
  • Labeling model training method and device

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Embodiment Construction

[0061]Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0062] like figure 1 As shown, the embodiment of the present application provides a labeling model training method, including:

[0063] Step S11: using the first sample with reference labels to train the initial labeling model to obtain the first labeling model.

[0064] Step S12: Use the first annotation model to annotate the second sample to obtain the second samp...

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Abstract

The invention discloses a labeling model training method and device, and relates to the field of computers, in particular to the field of data processing. The specific implementation scheme is as follows: training an initial labeling model by utilizing a first sample with a reference label to obtain a first labeling model; labeling the second sample by utilizing the first labeling model to obtaina second sample with model labeling; obtaining a third sample with a reference label, wherein the third sample is a part of the second sample; and optimizing the first annotation model according to the second sample with the model annotation and the third sample with the reference annotation. The data volume required by model training can be reduced, so that the manual operation amount and the time cost are saved.

Description

technical field [0001] The present application relates to the field of computers, in particular to the field of data processing. Background technique [0002] Image annotation is an important means of quality inspection. Traditional image annotation relies on the annotation operations of image annotators. In the quality inspection scenario, the amount of image data is very large, relying on the labeling operations of the labelers will consume a lot of manpower and the efficiency is very low. At the same time, there is a high possibility of errors in manual labeling. As the number of images for quality inspection increases, it is necessary to provide a more effective image annotation method. Contents of the invention [0003] In order to solve at least one problem in the prior art, embodiments of the present application provide a method and device for training a labeling model. [0004] In the first aspect, the embodiment of the present application provides a labeling mo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/21G06F18/214
Inventor 冷家冰赵景苏业聂磊矫函哲刘明浩郭江亮李旭
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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