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Improved YOLOX-based ancient building fire-fighting dangerous article rapid detection method and device

A technology for dangerous goods and detection methods, applied in the field of image processing, can solve the problems of low efficiency and low accuracy, and achieve the effect of lightweight model, easy construction, and rapid detection.

Inactive Publication Date: 2021-12-28
UNIV OF SCI & TECH BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a method and device for rapid detection of fire hazards in ancient buildings based on improved YOLOX to solve the technical problems of low efficiency and low accuracy of traditional manual detection methods

Method used

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  • Improved YOLOX-based ancient building fire-fighting dangerous article rapid detection method and device
  • Improved YOLOX-based ancient building fire-fighting dangerous article rapid detection method and device
  • Improved YOLOX-based ancient building fire-fighting dangerous article rapid detection method and device

Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0052] Aiming at the technical problem that the traditional manual detection method is not only low in efficiency but also low in accuracy, this embodiment provides a rapid detection method for ancient building fire hazards based on improved YOLOX, which aims to replace the existing manual detection method and realize the Real-time, multi-scale and high-precision detection of fire hazards. The method can be implemented by an electronic device. The execution flow of this method is as follows figure 1 shown, including the following steps:

[0053] S1, the YOLOX model framework is improved in a preset way to improve the accuracy of the model for multi-scale object detection and reduce the time-consuming detection, and the improved YOLOX model framework is obtained;

[0054] S2, train the improved YOLOX model framework to obtain the ancient building fire hazard detection model; wherein, the input of the ancient building fire hazard detection model is the item image, and the outp...

no. 2 example

[0093] The present embodiment provides a kind of ancient building fire-fighting dangerous article rapid detection device based on improved YOLOX, and this ancient building fire-fighting dangerous article rapid detection device based on improved YOLOX includes the following modules:

[0094] The model improvement module is used to improve the YOLOX model framework in a preset way, so as to improve the accuracy of the model for multi-scale object detection and reduce the time-consuming detection, and obtain an improved YOLOX model framework;

[0095] The model training module is used to train the YOLOX model framework improved by the model improvement module to obtain the ancient building fire-fighting dangerous article detection model; wherein, the input of the ancient building fire-fighting dangerous article detection model is an article image, and the output is an article type;

[0096] The item detection module is configured to classify the ancient building fire-fighting dan...

no. 3 example

[0099] This embodiment provides an electronic device, which includes a processor and a memory; at least one instruction is stored in the memory, and the instruction is loaded and executed by the processor, so as to implement the method of the first embodiment.

[0100] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) and one or more memories, wherein at least one instruction is stored in the memory, so The above instruction is loaded by the processor and executes the above method.

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Abstract

The invention discloses an improved YOLOX-based ancient building fire-fighting dangerous article rapid detection method and device, wherein the method comprises the steps: improving a YOLOX model frame in a preset manner, so as to improve the precision of multi-scale object detection and reduce the detection time, and obtaining an improved YOLOX model framework; training the improved YOLOX model framework to obtain an ancient building fire-fighting dangerous article detection model, wherein the input of the ancient building fire-fighting dangerous article detection model is an article image, and the output is an article type; and based on the ancient building fire-fighting dangerous article detection model, classifying to-be-detected ancient building fire-fighting dangerous articles according to the images of the to-be-detected ancient building fire-fighting dangerous articles. According to the invention, real-time rapid detection of multi-scale and multi-type fire-fighting dangerous articles is realized, the detection precision is improved, and lightweight deployment of an embedded system is realized.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method and device for quickly detecting fire hazards in ancient buildings based on improved YOLOX. Background technique [0002] Ancient buildings are the crystallization of the wisdom of the ancient working people, and have high cultural relic, historical and artistic values. However, the fire safety situation of ancient buildings is very serious, and the occurrence of various fires has sounded the alarm for the fire safety work of cultural relics and ancient buildings. The detection of fire hazards in ancient buildings is an important means to prevent fires. However, the traditional manual detection method is not only inefficient but also low in accuracy. Contents of the invention [0003] The invention provides a method and device for rapid detection of fire-fighting dangerous articles in ancient buildings based on improved YOLOX to solve the technical pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/214G06F18/24
Inventor 陈小龙黄国忠高学鸿王宇林琳
Owner UNIV OF SCI & TECH BEIJING