An Improved Fire and Smoke Detection Method Based on YOLOv7-Reference-Cited by-同舟云学术

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An Improved Fire and Smoke Detection Method Based on YOLOv7

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 32nd International Conference on Computer Communications and Networks (ICCCN)
language:
Short-container-title:

Author:

Lian Jie¹,Pan Xinyu²,Guo Jin³

Affiliation:

1. Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University,Shanghai,China

2. Shanghai Normal University,Department of Computer Science,Shanghai,China

3. Morgan State University,Department of Computer Science,Maryland,USA

Funder

Natural Science Foundation of Shanghai

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10230087/10230088/10230135.pdf?arnumber=10230135

Reference27 articles.

1. Deep Residual Learning for Image Recognition

2. Very deep convolutional networks for large-scale image recognition;simonyan;ArXiv Preprint,2014

3. ImageNet classification with deep convolutional neural networks

4. Deep convo-lutional neural networks for forest fire detection;zhang;2016 International Forum on Management Education and Information Technology Application,2016

5. Deep Convolutional Neural Networks for Fire Detection in Images

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. YOLOFM: an improved fire and smoke object detection algorithm based on YOLOv5n;Scientific Reports;2024-02-24

2. A lightweight early forest fire and smoke detection method;The Journal of Supercomputing;2023-12-18

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