Traffic target detection method and system based on improved YOLOv4

A target detection and detection method technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as difficulty in model deployment, calculation speed, difficulty in obtaining anchor frame configuration, large amount of model parameters, etc., to reduce the complexity of the model Accuracy, high accuracy, and high detection accuracy

Pending Publication Date: 2022-05-13
CHINA UNIV OF MINING & TECH
View PDF3 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] For the defects of the prior art, the object of the present invention is to propose a traffic target detection method and system based on improved YOLOv4, which can solve the following problems that YOLOv4 can produce in the single-stage target detection algorithm in the prior art: (1 ) sm

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
  • Traffic target detection method and system based on improved YOLOv4
  • Traffic target detection method and system based on improved YOLOv4
  • Traffic target detection method and system based on improved YOLOv4

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0141] Carry out traffic target detection through the detection system described in the above specific implementation mode, set the initial learning rate to 0.001, the learning rate attenuation coefficient to 0.96, the number of training rounds to 200 rounds, and the batchsize to 8. The obtained detection results are as attached Figure 8 As shown, it can be seen that the system can accurately detect targets of different sizes.

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 traffic target detection method and system based on improved YOLOv4, the detection system comprises a MobileViT-S backbone network, an SPP feature pyramid network, a PANet feature enhancement network and a target detection head, and convolution used in the PANet feature enhancement network and the target detection head is deep separable convolution. The method can be used for detecting pedestrians, vehicles and traffic light targets in an intelligent traffic scene, high detection accuracy is achieved on the basis of light weight, the omission ratio is low, and the detection effect is good.

Description

technical field [0001] The present invention relates to the technical field of computer vision, in particular to the technical field of target detection based on the YOLOv4 algorithm. Background technique [0002] With the rapid development of computer vision, object detection is gradually applied to people's daily life, which brings great convenience. Among them, in order to solve various traffic problems under complex traffic conditions, the detection of traffic objects has become a research focus in the field of computer vision. [0003] The targets in the traffic background have the characteristics of large number, severe occlusion, and mostly small targets. In the current background, target detection often has the disadvantages of serious missed detection, slow detection rate, and difficult deployment. Therefore, it is particularly important to optimize the target detection model to make it lightweight for easy deployment, speed up detection, and make it more suitable ...

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): G06V20/54G06V10/762G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/23213Y02T10/40
Inventor 袁小平王准赵耀倪梓昂李元博孙乐义
Owner CHINA UNIV OF MINING & TECH
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