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Method and device for training image recognition model and image recognition

A technology for identifying models and training images, applied in the fields of artificial intelligence, deep learning, and computer vision.

Active Publication Date: 2022-06-07
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the features used for supervision are still limited in their expressive power because of the small network

Method used

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  • Method and device for training image recognition model and image recognition
  • Method and device for training image recognition model and image recognition
  • Method and device for training image recognition model and image recognition

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Embodiment Construction

[0021] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding and should be considered 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 present disclosure. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

[0022] figure 1 An exemplary system architecture 100 is shown to which the method for training an image recognition model, the apparatus for training an image recognition model, the method for image recognition, or the apparatus for image recognition according to the embodiments of the present application may be applied.

[0023] like figure 1 As shown, the system...

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Abstract

The disclosure provides a method and device for training an image recognition model and image recognition, and relates to the field of artificial intelligence, especially to the fields of deep learning and computer vision. The specific implementation plan is: obtain the labeled sample set, unlabeled sample set and knowledge distillation network; perform the following training steps: select input samples from the labeled sample set and unlabeled sample set, and accumulate the number of iterations; input The samples are respectively input into the student network and the teacher network of the knowledge distillation network, and the student network and the teacher network are trained; if the training completion conditions are met, the image recognition model is selected from the student network and the teacher network. Through this embodiment, the amount of manual labeling can be reduced and the performance of the model can be improved.

Description

technical field [0001] The present disclosure relates to the field of artificial intelligence, in particular to the fields of deep learning and computer vision, and in particular to a training image recognition model and a method and apparatus for image recognition. Background technique [0002] In the field of image classification, there are many mature methods of knowledge distillation methods, which basically let the student network learn the soft label output or feature map of the teacher network. However, in the OCR (Optical Character Recognition, Optical Character Recognition) recognition task, the application of knowledge distillation is currently rare. For the CRNN (Convolutional Recurrent Neural Network, Convolutional Recurrent Neural Network) model, the soft label of the student network is directly distilled. , the effect is not as high as the accuracy of training directly based on the annotation information. In addition, during distillation, a teacher network wit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V30/413G06V10/774G06V10/82G06K9/62G06N3/04
CPCG06V30/413G06V30/10G06N3/045G06F18/214G06N3/084G06N3/08G06N3/042
Inventor 郭若愚杜宇宁李晨霞郜廷权赵乔刘其文毕然胡晓光于佃海马艳军
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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