Optimization method and system of target detection model

A technology of target detection and optimization method, which is applied in the field of computer vision, can solve problems such as increased calculation amount and inability to circulate information, and achieve the effect of reducing calculation amount and enhancing representation ability

Pending Publication Date: 2021-06-04
江苏禹空间科技有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It can be seen that the calculation amount of point-by-point convolution is proportional to the number of output channels N, and the number of output channels will continue to increase as the number of network layers deepens, which directly leads to a gradual increase in the calculation amou

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
  • Optimization method and system of target detection model
  • Optimization method and system of target detection model
  • Optimization method and system of target detection model

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0036] The technical solutions of the present disclosure will be described in detail below with reference to the accompanying drawings. In the description of the present disclosure, it should be understood that the terms "first", "second" and "third" are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implicitly indicating the indicated technology The number of features, used only to distinguish different components.

[0037] Figure 4 is the flow chart of the method of the present invention, such as Figure 4 As shown, the optimization method for the target detection model includes: Step S101 : Divide the image into M feature maps with dimensions of H×W×C, where C represents the depth of the feature map. H×W is used in this application to represent the size of feature maps or convolution kernels.

[0038] Step S102: Divide each feature map into N features, and each feature contains 1 / N features of each featur...

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 optimization method and system of a target detection model, relates to the technical field of computer vision, and solves the technical problems that the number of output channels of a convolutional network is large, the calculation amount of a convolution process is large, and the representation capability is not strong.According to the technical scheme, an image is divided into a plurality of feature maps; the features of the feature maps are divided, the features of the different feature maps are jointly input into a shuffling channel, all the features are shuffled, the input channel and the output channel are completely related through uniform combination of the different features, and the characterization capacity is enhanced. The number of the convolution kernels is smaller than the number of the feature maps, and the number of output channels is reduced, so that the calculated amount of the convolution kernel in the convolution process is reduced.

Description

technical field [0001] The present disclosure relates to the technical field of computer vision, in particular to a method and system for optimizing a target detection model. Background technique [0002] The convolutional neural network for mobile vision applications is one of the lightweight networks. This network is mainly used in mobile and embedded devices. The biggest feature of this network is the application of deep point-by-point convolutional networks and the addition of two Hyperparameters, one is a hyperparameter that controls the number of convolution kernels in the convolutional layer, and the other is a hyperparameter that controls the size of the input image. [0003] The characteristics of the standard convolutional network are: the depth of the convolution kernel is equal to the depth of the input feature matrix, and the depth of the output feature matrix is ​​equal to the number of convolution kernels. For example, if you input a feature matrix with a dep...

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): G06T7/10G06T5/50G06N3/04
CPCG06T7/10G06T5/50G06T2207/20021G06N3/045
Inventor 王堃
Owner 江苏禹空间科技有限公司
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