Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Network integration training method and device, electronic equipment and storage medium

A technology of network integration and training methods, which is applied in the fields of electronic equipment and storage media, image detection methods and devices, video processing methods and devices, and can solve the deviation between processing performance and expected requirements, no technical solutions, low processing performance, etc. problem, to achieve the effect of improving network processing performance, good feature fusion results, and improving processing performance

Inactive Publication Date: 2020-02-14
SHENZHEN SENSETIME TECH CO LTD
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the processing performance of multiple deep learning neural networks varies from high to low, and there is a gap between them, especially in the case of a large gap in processing performance, which will lead to a large deviation between the processing performance of the final network integration and the expected demand.
It can be seen that the current network integration method is not ideal, however, there is no effective solution in related technologies

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
  • Network integration training method and device, electronic equipment and storage medium
  • Network integration training method and device, electronic equipment and storage medium
  • Network integration training method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0144] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0145] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

[0146] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein mean...

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 a network integration training method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a to-be-trained first target networkwhich comprises at least two to-be-integrated networks connected in a bridging mode; and training the first target network according to the respective losses of the at least two networks to be integrated and a target loss function obtained by the overall loss of the first target network to obtain a trained second target network. The network processing performance of the second target network obtained after network integration is improved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, and in particular to a training method and device for network integration, an image classification method and device, an image detection method and device, a video processing method and device, electronic equipment, and a storage medium. Background technique [0002] Network integration of multiple deep learning neural networks can improve the overall processing performance of the network. Taking the image classification scene as an example, image classification is the basis of computer vision, and the classification performance (such as classification accuracy) of image classification can be improved through network integration. However, the processing performance of multiple deep learning neural networks varies from high to low, and there is a gap between them. Especially in the case of a large gap in processing performance, the processing performance of the final netwo...

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): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V2201/07G06N3/045G06F18/241G06F18/253
Inventor 李艺段逸群孙鹏宇旷章辉陈益民张伟
Owner SHENZHEN SENSETIME TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com