Subway security check method based on combination of CPSNet and yolov3

A combination and security inspection technology, applied in the field of medical image bone segmentation, can solve the problem of low detection accuracy, achieve the effect of improving detection accuracy, good detection effect, and various performance metrics

Pending Publication Date: 2021-03-16
SOUTHEAST UNIV
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Moreover, compared with other detection networks, yolov3 has greatly improved the detection speed, but the detection accuracy is relatively low. In order t

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
  • Subway security check method based on combination of CPSNet and yolov3
  • Subway security check method based on combination of CPSNet and yolov3
  • Subway security check method based on combination of CPSNet and yolov3

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0023] Embodiment: a subway security image detection method based on the combination of CPSNet and yolov3, the specific steps are as follows:

[0024] Step 1, select yolov3 as the main network, use CPSNet to replace the feature extraction network of darknet53 of the original yolov3, and combine them to build a new neural network: use csresnext as the feature extraction network to extract a more complete feature map as the input of the detection network;

[0025] Step 2, using self-collected images as training samples to train the new neural network built in step 1;

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 a subway security check method based on the combination of CPSNet (csresnextpanetspp) and yolov3, and the method comprises the steps: enabling the CPSNet to be integrated intothe yolov3 to form a new network structure, carrying out the training through employing a self-collected subway security check image, and marking and recognizing dangerous goods and auxiliary detection goods in a subway security check image. According to the invention, a novel neural network structure is used and intelligent identification of a complex subway security check image is realized.

Description

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

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
Owner SOUTHEAST UNIV
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