Image recognition model training method and device, image recognition method and device, and electronic equipment

A technology of image recognition and model training, applied in the computer field, can solve the problems of low efficiency of manual labeling

Pending Publication Date: 2020-07-31
杭州网易智企科技有限公司
View PDF4 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when the types of objects that need to be identified rise to thousands or tens of thousands, the efficiency of manual labeling is extremely low

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 model training method and device, image recognition method and device, and electronic equipment
  • Image recognition model training method and device, image recognition method and device, and electronic equipment
  • Image recognition model training method and device, image recognition method and device, and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0127]The principle and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present application, rather than to limit the scope of the present application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0128] Those skilled in the art know that the embodiments of the present application may be realized as a system, device, device, method or computer program product. Therefore, the present disclosure may be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0129] Herein, it should be understood that any number of elements in the drawings is ...

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 discloses an image recognition model training method and device, an image recognition method and device, electronic equipment and a storage medium. A large number of marked training samples can be quickly generated, the training cost is reduced, and the training efficiency is improved. The image recognition model training method comprises the steps: extracting a mapping template containing an identifier from a first image containing the identifier; adding the mapping template into the plurality of second images to obtain a plurality of sample images; taking the sample image and alabeling label corresponding to the sample image as training samples and adding the training samples into a training sample set, wherein the labeling label is determined based on an identifier category to which an identifier contained in a mapping template in the sample image belongs; and training an image recognition model based on the training sample set to obtain an image recognition model capable of recognizing the identifier category to which the identifier contained in the image belongs.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an image recognition model training and image recognition method, device, and electronic equipment. Background technique [0002] This section is intended to provide a background or context to the implementations of the application that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] Existing methods for training image recognition models usually include manually labeling the objects contained in the images, and using the labeled images as training samples to train the image recognition model. However, when the number of objects to be recognized increases to thousands or tens of thousands, the efficiency of manual labeling is extremely low. Contents of the invention [0004] In view of the above technical problems, an improved method is very much needed, which can quickly generate a large nu...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/241G06F18/214
Inventor 胡宜峰吕玥吕晓新李雨珂杨卫强朱浩齐
Owner 杭州网易智企科技有限公司
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap