Image detection model training method and device and storage medium

A technology of image detection and training methods, applied in the field of machine learning, which can solve the problems of difficult convergence of training tasks and low model accuracy

Active Publication Date: 2019-11-12
BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present disclosure provides a training method, device and system for an image detection model to at least solve the problems in the related art that in the case of unbalanced samples, the training task is difficult to converge, and the accuracy of the trained model is not high when used for image detection. question

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  • Image detection model training method and device and storage medium
  • Image detection model training method and device and storage medium
  • Image detection model training method and device and storage medium

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Embodiment Construction

[0070] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0071] It should be noted that the terms "first" and "second" in the specification and claims of the present disclosure 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 that the embodiments of the disclosure described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consi...

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Abstract

The invention relates to an image detection model training method and device and a storage medium, and the method comprises the steps: obtaining a sample image set for training a target model; determining a category regression loss function of the target model for a target sample image according to the number of samples corresponding to different sample categories contained in the sample image setand the prediction probability of the target model for the currently input target sample image; and for each sample image in the sample image set, adjusting a category regression loss function of thetarget model, and training model parameters in the target model through the sample images. The technical problems that under the condition that samples are unbalanced, training tasks are difficult toconverge, and the accuracy and recall rate of a model obtained through training are not high are solved. The method has the advantages that the convergence speed of the sample categories with the small sample number is increased, and the accuracy and recall rate of the model obtained through training are increased.

Description

technical field [0001] The present disclosure relates to the technical field of machine learning, and in particular to a training method, device and storage medium for an image detection model. Background technique [0002] With the rapid development of artificial intelligence, the scope of application of network models is becoming wider and wider. For example, image recognition, text recognition, etc. can be performed through the model. Moreover, when applying the model to different scenarios, it is necessary to train the model parameters of the model in the current application scenario accordingly. [0003] In related technologies, the traditional image detection model training process will assign the same weight to each sample image. Therefore, in the case of unbalanced training sample images, the training task is difficult to converge. The precision and recall are not high either. Taking OCR (Optical Character Recognition, Optical Character Recognition) as an example,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/214
Inventor 张水发李岩王思博刘畅
Owner BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
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