Research on fire detection based on YOLOv5
Author:
Affiliation:
1. Leshan Vocational and Technical College,Leshan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9985779/9985780/09985857.pdf?arnumber=9985857
Reference8 articles.
1. YOLO9000: Better, Faster, Stronger
2. You Only Look Once: Unified, Real-Time Object Detection
3. Fire Smoke Detection Algorithm Based on Motion Characteristic and Convolutional Neural Networks;luo;Multimedia Tools and Applications,2019
4. Convolutional neural network for video fire and smoke detection
5. Smoke Detection on Video Sequences Using 3D Convolutional Neural Networks
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1. ESFD-YOLOv8n: Early Smoke and Fire Detection Method Based on an Improved YOLOv8n Model;Fire;2024-08-27
2. Design and Development of Fire Fighting UAV for Urban Environments;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26
3. Computer vision for wildfire detection: a critical brief review;Multimedia Tools and Applications;2024-03-13
4. FIREnet 2.0: Advanced Neural Framework for Smart Fire Detection & Localization;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11
5. Paper Deep Learning - An Investigation on Fire and Fire's Losses Detection Using YOLOv5;2023 24th International Arab Conference on Information Technology (ACIT);2023-12-06
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