A survey on vision-based outdoor smoke detection techniques for environmental safety

Author:

Chaturvedi Shubhangi,Khanna Pritee,Ojha Aparajita

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference197 articles.

1. Unsupervised segmentation of fire and smoke from infra-red videos;Ajith;IEEE Access,2019

2. Combining multi-channel color space with local binary co-occurrence feature descriptors for accurate smoke detection from surveillance videos;Alamgir;Fire Saf. J.,2018

3. ALERTWildfire, Wildfire hazard potential (whp) for the conterminous united states (270-m grid), version 2018 classified (2nd edition). usda forest service, http://www.alertwildfire.org//, [Online; accessed 08-07-2021].

4. Aslan, S., Güdükbay, U., Töreyin, B.U., Çetin, A.E., 2019. Early wildfire smoke detection based on motion-based geometric image transformation and deep convolutional generative adversarial networks. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp. 8315–8319.

5. Avgerinakis, K., Briassouli, A., Kompatsiaris, I., 2012. Smoke detection using temporal hoghof descriptors and energy colour statistics from video. In: International Workshop on Multi-sensor Systems and Networks for Fire Detection and Management.

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