A forest smoke recognition system based on deep learning

Jinghao Gong; Xiaofei Yan; Yanqiu Wang

doi:10.1117/12.3045780

9 October 2024 A forest smoke recognition system based on deep learning

Jinghao Gong, Xiaofei Yan, Yanqiu Wang

Proceedings Volume 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024); 132881M (2024) https://doi.org/10.1117/12.3045780
Event: Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 2024, Chengdu, China

Abstract

Forests, as vital ecological resources of the Earth, frequently witness devastating wildfires that pose enormous threats to the environment, ecosystems, and human life. To mitigate the losses caused by forest fires, it is imperative to enhance fire prediction and control measures, with video surveillance technology playing a pivotal role in fire watch. Focusing on the extraction of prominent features from wildfire videos and the application of deep learning techniques, the system employs unmanned aerial vehicles (UAVs) to acquire navigational video data in forest areas, integrating multiple payloads for real-time forest fire detection. The project enhances methods for identifying smoke from forest fires in videos, ensuring a stable and reliable forest fire monitoring system alongside real-time data acquisition.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinghao Gong, Xiaofei Yan, and Yanqiu Wang "A forest smoke recognition system based on deep learning", Proc. SPIE 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 132881M (9 October 2024); https://doi.org/10.1117/12.3045780

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available