NDLI: Channel-wise attention model-based fire and rating level detection in video

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Channel-wise attention model-based fire and rating level detection in video

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Channel-wise attention model-based fire and rating level detection in video

Content Provider	IET Digital Library
Author	Wu, Yirui He, Yuechao Shivakumara, Palaiahnakote Li, Ziming Guo, Hongxin Lu, Tong
Abstract	Due to natural disaster and global warning, one can expect unexpected fire, which causes panic among people and extent to death. To reduce the impact of fire, the authors propose a new method for predicting and rating fire in video through deep-learning models in this work such that rescue team can save lives of people. The proposed method explores a hybrid deep convolutional neural network, which involves motion detection and maximally stable extremal region for detecting and rating fire in video. Further, the authors propose to use a channel-wise attention mechanism of the deep neural network for detecting rating of fire level. Experimental results on a large dataset show the proposed method outperforms the existing methods for detecting and rating fire in video.
Starting Page	117
Ending Page	121
Page Count	5
Volume Number	4
e-ISSN	24682322
Issue Number	Issue 2, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/trit/4/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/trit.2019.0022
Journal	CAAI Transactions on Intelligence Technology
Publisher	The Institution of Engineering and Technology Chongqing University of Technology Chinese Association for Artificial Intelligence
Publisher Date	2019-04-24
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Channel-wise Attention Mechanism Channel-wise Attention Model-based Fire Computer Vision And Image Processing Technique Deep Neural Network Deep-learning Model Feature Extraction Fire Level Global Warning Hybrid Deep Convolutional Neural Network Knowledge Engineering Technique Learning in AI Maximally Stable Extremal Region Motion Detection Natural Disaster Neural Computing Technique Neural Nets Rating Rescue Team Unexpected Fire
Content Type	Text
Resource Type	Article

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