Model training method and terminal equipment

A technology of model training and training data, which is applied in the computer field, can solve the problems of long training period and low efficiency of model training, and achieve the effects of improving training efficiency, enhancing effect, improving robustness and accuracy

Pending Publication Date: 2020-03-10
TCL CORPORATION
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] In view of this, the embodiment of the present invention provides model training and terminal equipment to solve the current problem of lon

Method used

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  • Model training method and terminal equipment
  • Model training method and terminal equipment
  • Model training method and terminal equipment

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Embodiment Construction

[0028] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0029] In order to illustrate the technical solutions of the present invention, specific examples are used below to illustrate.

[0030] figure 1 The implementation flowchart of the model training method provided by the embodiment of the present invention is described in detail as follows:

[0031] In S101, a model to be trained and training data are obtained; the training data includes a plural...

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Abstract

The invention relates to the technical field of computers, and provides a model training method and terminal equipment. The method comprises the steps of obtaining a to-be-trained model and training data; wherein the training data comprises a plurality of samples, and each sample corresponds to a probability value; selecting a plurality of samples from the training data according to the probability value of each sample to generate a training data set; training the to-be-trained model through the training data set, and obtaining an recognition result of the to-be-trained model for the trainingdata set; calculating a clustering effect evaluation value of the training data set according to the recognition result and the training data set; and adjusting the probability value corresponding toeach sample in the training data set according to the clustering effect evaluation value. According to the method, model training and training data screening are combined, so that the training efficiency of model training can be improved; in the training iteration process, the effect of difficult-to-recognize samples on model training can be enhanced, and then the robustness and accuracy of the trained model are improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a model training method and terminal equipment. Background technique [0002] Artificial intelligence technology needs to use a large amount of training data for model training. Taking artificial intelligence face recognition technology as an example, if you want to train a model with superior performance, you need millions of face pictures at every turn. A large number of face pictures requires a lot of manpower and material resources to manually collect and clean up the faces of different people. Due to factors such as human eye fatigue, there may be wrong pictures in a large number of manually collected pictures, resulting in many noisy pictures in the pictures in the training set. [0003] In addition, there are some face pictures in the training data, which may be difficult to recognize due to lighting, shooting angles, etc. However, in practical applications, f...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2321G06F18/24G06F18/214
Inventor 蒋佳
Owner TCL CORPORATION
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