Clustering model training method and device, electronic equipment and computer storage medium

A training method and a technology of a training device, which are applied in the field of computer vision and can solve problems such as loss of correction information and waste of resources

Active Publication Date: 2018-06-29
BEIJING SENSETIME TECH DEV CO LTD
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this will lose the correction information of the previous clus

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
  • Clustering model training method and device, electronic equipment and computer storage medium
  • Clustering model training method and device, electronic equipment and computer storage medium
  • Clustering model training method and device, electronic equipment and computer storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0111] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangements of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0112] At the same time, it should be understood that, for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0113] The following description of at least one exemplary embodiment is merely illustrative in nature and in no way taken as limiting the invention, its application or uses.

[0114] Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the descript...

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 embodiment of the invention discloses a clustering model training method and device, electronic equipment and a computer storage medium. The method includes the steps that clustering is conductedon new photos through a clustering model and clustered photos to obtain a clustering result of the new photos, wherein the new photos carry class labels; the return function value of the clustering result is calculated based on the clustering result of the new photos and the class labels; the clustering model is trained according to the return function value of the clustering result. According tothe embodiment, the new photos and photos in an initial-state photo album with a classifying result are clustered through the trained clustering model, the obtained clustering result is closer to a manual classifying result, and the clustering accuracy of the trained clustering model is higher.

Description

technical field [0001] The invention relates to computer vision technology, in particular to a training method, device, electronic equipment and computer storage medium of a clustering model. Background technique [0002] The current smart album can automatically mark and cluster the photos in the album based on face recognition technology. [0003] However, for the smart album that has been clustered, in practical applications, users will continue to add new photos. In the process of adding new photos to the smart album that has been clustered, incremental clustering is required. Re-cluster the newly added photos and the clustered photos. Currently, all photos (including newly added photos and clustered photos) are generally re-clustered to achieve incremental clustering. However, this will lose the correction information of the previous clustering results, and frequent re-clustering will cause waste of resources. Contents of the invention [0004] An embodiment of the...

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): G06F17/30G06K9/62
CPCG06F16/583G06F18/23G06F18/2411G06F18/214
Inventor 曹凯迪何悦李诚
Owner BEIJING SENSETIME TECH DEV 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

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