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Data annotation detection method and device

A detection method and target detection technology, applied in the field of data labeling, can solve the problems affecting the accuracy of labeling results, and the quality inspection of labeling results cannot be achieved, achieving high accuracy and improving accuracy

Active Publication Date: 2020-04-28
北京云聚智慧科技有限公司
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AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a detection method and device for data labeling, which is used to solve the problem that when the quality inspection personnel perform quality inspection on the labeling results, it is impossible to comprehensively check out the labeling results with wrong labels or missing labels, thus affecting the accuracy of the labeling results rate problem

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  • Data annotation detection method and device
  • Data annotation detection method and device

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Embodiment Construction

[0033] After the labeling personnel label the image data, they can perform quality inspection on the labeling results to determine whether there is any wrong labeling or missing labeling, so as to improve the accuracy of the labeling results. At present, random sampling is usually used for quality inspection of manual labeling results. Specifically, quality inspectors can randomly select several images and their labeling results for review, determine whether there are missing or wrong labeling results in the labeling results, and when determining that there are missing or wrong labeling results, Correct the labeling results with missing or wrong labels, so as to improve the accuracy of the labeling results.

[0034] However, the random sampling method cannot fully detect the missing or wrong labeling problems, which may affect the accuracy of the labeling results.

[0035] In order to comprehensively check the quality of the manual labeling results, at present, the method of ...

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Abstract

The invention discloses a data annotation detection method and device. The method comprises the steps: obtaining a target image and a manual annotation result obtained after the manual annotation of the target image, and the manual annotation result comprises the types and coordinates of a plurality of first objects; identifying the target image according to a predetermined target recognition model to obtain a target annotation result, the target annotation result comprising categories and coordinates of a plurality of second objects, and the target recognition model being obtained by trainingthe categories and coordinates of a plurality of sample objects obtained by annotating the sample image on the basis of a target detection network; According to the manual annotation result and the target annotation result, determining whether a wrong annotation result exists in the manual annotation result or not. Thus, since the accuracy of the recognition result of the target recognition modelis high, the target annotation result is used as a quality inspection standard, quality inspection personnel can be effectively helped to comprehensively detect wrong manual annotation results, and the accuracy of data annotation is improved.

Description

technical field [0001] The present application relates to the field of data labeling, and in particular to a data labeling detection method and device. Background technique [0002] At present, in order to achieve the purpose of image recognition based on artificial intelligence, annotators can label a large number of images, so that the machine for artificial intelligence recognition can learn the features in the image according to the labeling results, so as to recognize the image. [0003] After labeling the images, in order to ensure the accuracy of the labeling results, quality inspection personnel are usually required to conduct quality inspections on the labeling results of the labeling personnel to determine whether there is a problem of missing or wrong labeling, and to determine whether there are missing labels In the event of problems or wrong labeling, correct the labeling results in time, thereby improving the accuracy of the labeling results. [0004] However,...

Claims

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Application Information

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IPC IPC(8): G06F16/51G06F16/58G06K9/00G06N20/00
CPCG06F16/51G06F16/5866G06N20/00G06V20/10
Inventor 秦星达
Owner 北京云聚智慧科技有限公司
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