Research on Gas Pipeline Fire Detection Algorithm Based on Improved YOLOv8

The improved gas pipeline fire detection algorithm based on YOLOv8n plays a crucial role in the safety monitoring and fire warning system of gas pipelines, enhancing the detection rate and response speed of fire, effectively reducing human and financial losses caused by fire. This study established...

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Bibliographic Details
Published in2024 IEEE 7th International Conference on Electronic Information and Communication Technology (ICEICT) pp. 1298 - 1301
Main Authors Ye, Yiting, Chang, Haiqing, Xiang, Boqing
Format Conference Proceeding
LanguageEnglish
Published IEEE 31.07.2024
Subjects
Accuracy
Annotations
BiFPN
Fire detection
Fires
Focal DIoU Loss
Information and communication technology
Object detection
Pipelines
Safety
YOLOv8
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Summary:The improved gas pipeline fire detection algorithm based on YOLOv8n plays a crucial role in the safety monitoring and fire warning system of gas pipelines, enhancing the detection rate and response speed of fire, effectively reducing human and financial losses caused by fire. This study established a dataset of fire images, incorporated the BiFPN network into YOLOv8n, and introduced the Focal DIoU Loss for bounding box regression calculation. Compared to the unimproved YOLOv8n, this algorithm has achieved an increase in Precision by 0.16%, Recall rate by 3.36%, and mAP@0.5 by 1.36%.
ISSN:2836-7782
DOI:10.1109/ICEICT61637.2024.10671153