Image recognition and neural network model training method, device and system

A neural network model and image recognition technology, applied in the field of image processing, can solve problems such as easy misjudgment

Active Publication Date: 2019-08-23
MEGVII BEIJINGTECH CO LTD
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, face recognition based on the image features extracted by the above classification model has the problem of easy misjudgment

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Image recognition and neural network model training method, device and system
  • Image recognition and neural network model training method, device and system
  • Image recognition and neural network model training method, device and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0060] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0061] The image recognition method provided by this application can be applied, but not limited to, such as figure 1 shown in the application environment. Wherein, the photographing device 12 can obtain the image to be recognized, and send the image to be recognized to the computer device 11; the computer device 11 can extract the target image feature from the image to be recognized, and the image feature and background of the image to be recognized Compare the image features of the bottom library images in the library image group to obtain the comparison results for ima...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an image recognition and neural network model training method, device and system. The method comprises the steps of obtaining a to-be-identified image; inputting the to-be-identified image into the neural network model for feature extraction processing, and outputting a target image feature of the to-be-identified image in the feature space, wherein the neural network model is obtained by training based on a loss function including charge interaction potential energy, the charge interaction potential energy is related to distances between different image features in the feature space, and the charge interaction potential energy comprises charge attraction potential energy between the image features belonging to the same object and charge rejection potential energybetween the image features belonging to different objects; and performing image recognition processing on the target image features to obtain an image recognition result of the to-be-recognized image.By adopting the method, the image false identification rate can be reduced.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to an image recognition and neural network model training method, device, system and readable storage medium. Background technique [0002] At present, face recognition tasks are divided into three categories, face verification (verifying whether multiple face images correspond to the same person), face search (finding the image most similar to the face image to be recognized in multiple face images in the bottom library) ) and face image clustering (classifying multiple face images to be recognized). At present, the popular method is to perform different types of face recognition tasks by training deep network models to convert face images into points in feature space (feature space). On this basis, the face recognition task is equivalent to training a good deep network model, converting the face image to be recognized into points in the feature space, that is, ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06N3/08G06K9/00
CPCG06N3/08G06V40/168G06V40/172G06V20/10
Inventor 王塑李亮亮杜佳慧刘宇
Owner MEGVII BEIJINGTECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products