Enhancing real-time fire detection: an effective multi-attention network and a fire benchmark

Over the past decades, fire has been considered one of the most serious natural disasters because of its devastating nature, rapid spread, and high impact on the ecology, economy, environment, and life preservation. Therefore, early fire detection has immense significance in computer vision. However...

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Veröffentlicht in:	Neural computing & applications Jg. 37; H. 18; S. 11693 - 11707
Hauptverfasser:	Khan, Taimoor, Khan, Zulfiqar Ahmad, Choi, Chang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.06.2025 Springer Nature B.V
Schlagworte:	Artificial Intelligence Benchmarks Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer vision Data Mining and Knowledge Discovery Datasets Deep learning Feature maps Fire detection Forest & brush fires Image Processing and Computer Vision Inference Machine learning Modules Natural disasters Probability and Statistics in Computer Science Real time S.I.: Innovations in AI-based Systems and Software Sensors Special Issue on Innovations in AI-based Systems and Software Subject specialists Deep learning Disaster management system Attention module Fire detection Machine learning MAFire-Net
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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