Iteration method and device for identification model

A technology for identifying models and iterations, which is applied in the computer field and can solve the problems of low model identification accuracy.

Pending Publication Date: 2021-05-18
SHANGHAI MININGLAMP ARTIFICIAL INTELLIGENCE GRP CO LTD
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Problems solved by technology

[0004] The present application provides an iterative method and device for a recognition model to at least solve the tec

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  • Iteration method and device for identification model
  • Iteration method and device for identification model
  • Iteration method and device for identification model

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Embodiment Construction

[0048] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0049]It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such ...

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Abstract

The invention relates to an iteration method and device for a recognition model, and the method comprises the steps: obtaining a first training sample which comprises data and annotation information which have a corresponding relation and are wrongly recognized by a first recognition model, wherein the first recognition model is used for executing a data recognition task; training an initial model corresponding to the first recognition model by using the first training sample to obtain a second recognition model; adding the first training sample to a second training sample so as to obtain a third training sample, wherein the second training sample is used for training a sample of an initial model corresponding to the first recognition model; and training the second recognition model by using a third training sample to obtain a third recognition model which is used for continuing to execute the data recognition task. According to the method and the device, the technical problem that the model recognition accuracy obtained after iteration is performed on the recognition model is relatively low is solved.

Description

technical field [0001] The present application relates to the field of computers, in particular to an iterative method and device for identifying models. Background technique [0002] Deep learning models often recognize objects in the form of recognition pictures. The accuracy of this recognition model is not 100%, and sometimes recognition errors occur during the recognition process. These misidentified pictures are collected as data for training the model during model iteration. In the actual use of the deep learning recognition model, it will be found that these wrongly recognized pictures have higher value for model optimization. But the distribution of wrong pictures is not uniform, and as the model iterates, the data distribution keeps changing. If you simply add the wrong picture to the original picture set to retrain the model, it will not optimize the model very well. [0003] For the above problems, no effective solution has been proposed yet. Contents of the...

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Application Information

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IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/214
Inventor 翟步中
Owner SHANGHAI MININGLAMP ARTIFICIAL INTELLIGENCE GRP CO LTD
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