CN2VF-Net: A Hybrid Convolutional Neural Network and Vision Transformer Framework for Multi-Scale Fire Detection in Complex Environments

Fire detection remains a challenging task due to varying fire scales, occlusions, and complex environmental conditions. This paper proposes the CN2VF-Net model, a novel hybrid architecture that combines vision Transformers (ViTs) and convolutional neural networks (CNNs), effectively addressing these...

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主要な著者:	Naveed Ahmad, Mariam Akbar, Eman H. Alkhammash, Mona M. Jamjoom
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2025-05-01
シリーズ:	Fire
主題:	convolutional neural networks (CNNs) vision Transformers (ViTs) D-Fire Grad-CAM multi-scale attention mechanism
オンライン･アクセス:	https://www.mdpi.com/2571-6255/8/6/211
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