Vehicle detection method and device based on attention mechanism and feature weighted fusion

A vehicle detection and feature weighting technology, which is applied in the field of vehicle target detection, can solve the problems of large model parameters and insufficient precision, and achieve the effects of improving detection accuracy, fast detection speed, and reducing the amount of parameters

Pending Publication Date: 2022-01-04
UNIV OF SCI & TECH BEIJING +1
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a vehicle detection method and device based on attention mechanism and feature weighted fusion to solve the technical problems of insufficient precision and large amount of model parameters existing in existing vehicle detection technology

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
  • Vehicle detection method and device based on attention mechanism and feature weighted fusion
  • Vehicle detection method and device based on attention mechanism and feature weighted fusion
  • Vehicle detection method and device based on attention mechanism and feature weighted fusion

Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0058] This embodiment provides a vehicle detection method based on attention mechanism and feature weighted fusion, the implementation environment of the method is as follows figure 1 As shown, the implementation environment includes at least one terminal 101 and at least one server 102 for providing services for the terminal 101 . The terminal 101 is connected to the server 102 through a wireless or wired network, and the terminal 101 may be a computer or an intelligent terminal capable of accessing the server 102 . For the process of vehicle detection, the image to be recognized can be acquired by the terminal 101, and the vehicle detection model trained in advance is stored in the server 102. After the image to be recognized is obtained by the terminal 101, the image to be recognized is sent by the terminal 101 to the server 102, and then The image to be recognized is input into the vehicle detection model by the server 102, so that the vehicle detection model recognizes t...

no. 2 example

[0111] This embodiment provides a vehicle detection device based on attention mechanism and feature weighted fusion. The system structure of the vehicle detection device 800 is as follows Figure 8 As shown, the following modules are included:

[0112] A preprocessing module 801, configured to preprocess the image to be detected to obtain the preprocessed image to be detected;

[0113] A data input module 802, configured to input the image to be detected pre-processed by the pre-processing module 801 into the pre-trained vehicle detection model;

[0114] The attention feature map generation module 803 is used to use the vehicle detection model to generate channel attention features based on the preprocessed image to be detected input by the data input module 802, using a channel and space two-dimensional attention mechanism graph and spatial attention feature map;

[0115] The feature weighted fusion module 804 is used to perform differentiated feature fusion based on the ch...

no. 3 example

[0119] This embodiment provides an electronic device, such as Figure 9 As shown, the electronic device 900 may have relatively large differences due to different configurations or performances, including one or more than one processor (central processing units, CPU) 901 and one or more than one memory 902; wherein, the memory 902 stores There is at least one instruction, and the instruction is loaded and executed by the processor 901 to implement the method of the first embodiment.

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 vehicle detection method and device based on an attention mechanism and feature weighted fusion. The method comprises the following steps: preprocessing a to-be-detected image; inputting the preprocessed to-be-detected image into a pre-trained vehicle detection model; generating a channel attention feature map and a space attention feature map by using a vehicle detection model, based on the preprocessed to-be-detected image, and by adopting a channel and space two-dimensional attention mechanism; performing differentiated feature fusion based on the channel attention feature map and the space attention feature map through a weighted bidirectional feature fusion network, and obtaining fusion features; based on the fusion features, obtaining a detection result containing vehicle position and size information. Compared with the existing vehicle detection technology, the method has the advantages that the parameter quantity is reduced and the detection precision is improved while the relatively high detection speed is maintained, and particularly, the detection effect on small-scale vehicles is remarkable.

Description

technical field [0001] The invention relates to the technical field of vehicle target detection, in particular to a vehicle detection method and device based on attention mechanism and feature weighted fusion. Background technique [0002] Vehicle detection refers to the segmentation of image instances and scenes based on the geometric and statistical characteristics of vehicle targets in a given image or video sequence, determining the size and position information of the vehicle in the image, and outputting it in the form of a detection frame. [0003] Vehicle detection methods are mainly divided into traditional algorithms based on manual features and detection methods based on deep neural networks. In traditional algorithms, feature extraction relies on artificially designed features. The quality of artificially designed features directly determines the accuracy of target detection. For highway monitoring scenarios with complex and changeable environments and low video r...

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
CPCG06N3/084G06N3/045G06F18/253G06F18/214
Inventor 刘丽梁鹏雷雪梅邵立珍
Owner UNIV OF SCI & TECH BEIJING
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