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EARLY WILDFIRE SMOKE DETECTION BASED ON MOTION-BASED GEOMETRIC IMAGE TRANSFORMATION AND DEEP CONVOLUTIONAL GENERATIVE ADVERSARIAL NETWORKS
- Citation Author(s):
- 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
- Categories:
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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