Training method, data processing method and related products of neural network model

A neural network model and network model technology, which is applied in the field of computer applications, can solve the problems of high energy efficiency of processors and large floating-point data calculations, and achieve the effects of reduced calculations, improved efficiency, and improved performance

Active Publication Date: 2020-08-25
SHANGHAI CAMBRICON INFORMATION TECH CO LTD
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the traditional neural network model, data is processed in the form of floating-point data. However, due to the large amount of calculation of floating-point data, the energy efficiency of the processor is high.

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
  • Training method, data processing method and related products of neural network model
  • Training method, data processing method and related products of neural network model
  • Training method, data processing method and related products of neural network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present disclosure with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of them. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present disclosure.

[0065] It should be understood that the terms "first", "second", "third" and "fourth" in the specification and drawings of the present disclosure are used to distinguish different objects, rather than to describe a specific order. The terms "comprising" and "comprises" used in the specification and claims of this disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or more other features, intege...

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 application relates to a training method of a neural network model, a data processing method and related products. The method includes: obtaining an initial network model; wherein, the initial network model includes a plurality of network layers; the initial training input data is processed layer by layer to obtain the processed data corresponding to each of the network layers; according to the processed The data of the initial network model is trained to obtain the trained neural network model. By adopting the method, the computing overhead of the processor can be reduced.

Description

technical field [0001] This application relates to the field of computer application technology, in particular to a neural network model training method, data processing method and related products. Background technique [0002] With the development of neural network technology, the deep learning framework (Caffe) has been widely used. [0003] After training, the Caffe-based neural network model can process data such as images, voices, and texts to obtain the required recognition results, such as recognizing images to obtain image features, and recognizing voices to obtain control instructions. [0004] In the traditional neural network model, data is processed in the form of floating-point data. However, due to the large amount of calculation of floating-point data, the energy efficiency of the processor is high. Contents of the invention [0005] Based on this, it is necessary to provide a neural network model training method, a data processing method, a device, a proc...

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 Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62
CPCG06N3/08G06N3/045G06F18/241
Inventor 不公告发明人
Owner SHANGHAI CAMBRICON INFORMATION TECH 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