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EARLY WILDFIRE SMOKE DETECTION BASED ON MOTION-BASED GEOMETRIC IMAGE TRANSFORMATION AND DEEP CONVOLUTIONAL GENERATIVE ADVERSARIAL NETWORKS

Citation Author(s):
Suleyman Aslan, Ugur Gudukbay, Behçet Uğur Töreyin, Ahmet Enis Çetin
Submitted by:
Ahmet Cetin
Last updated:
10 May 2019 - 10:49pm
Document Type:
Presentation Slides
Document Year:
2019
Event:
Presenters:
Ahmet Enis Cetin
Paper Code:
SS-L20
 

Immediate and accurate detection of wildfire is essentially important in forest monitoring systems
•One of the most harmful hazards in rural areas
•For wildfire detection, the use of visible-range video captured by surveillance cameras are suitable
•They can be deployed and operated in a cost-effective manner
•The challenge is to provide a robust detection system with negligible false positive rates
•If the flames are visible, they can be detected by analyzing the motion and color clues of a video
•Modeling various spatio-temporal features and dynamic texture analysis have been shown to be able to detect fire as well

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