Fire Detection Algorithms Using Multimodal ... - Bilkent University
Fire Detection Algorithms Using Multimodal ... - Bilkent University Fire Detection Algorithms Using Multimodal ... - Bilkent University
CHAPTER 7. CONCLUSION AND FUTURE WORK 109each sensor. The proposed set theoretic framework can be used to actively adaptindividual sensor weights in accordance with the feedback from an oracle.
Bibliography[1] B. Albers and A. Agrawal. Schlieren analysis of an oscillating gas-jet diffusion.Combustion and Flame, 119:84–94, 1999.[2] H. Ammann, R. Blaisdell, M. Lipsett, S. Stone, S. Therriault, J. W. P.Jenkins, and K. Lynch. Wildfire smoke - A guide for public health officials,http://depts.washington.edu/wildfire/pubhlthguidev.9.0.pdf, Accessedat December 2008.[3] M. Bagci, Y. Yardimci, and A. Cetin. Moving object detection using adaptivesubband decomposition and fractional lower order statistics in videosequences. Signal Processing, pages 1941–1947, 2002.[4] I. Bosch, S. Gomez, L. Vergara, and J. Moragues. Infrared image processingand its application to forest fire surveillance. In Proceedings of the IEEEConference on Advanced Video and Signal Based Surveillance (AVSS), pages283–288, 2007.[5] J. A. Broadbent. Fundamental flame flicker monitoring for power plantboilers. In Proceedings of the IEE Seminar on Advanced Sensors and InstrumentationSystems for Combustion Processes, pages 4/1–4/4, 2000.[6] H. Bunke and T. C. (Eds.). HMMs Applications in Computer Vision. WorldScientific, 2001.[7] F. Carter and N. Cross. Combustion monitoring using infrared array-baseddetectors. Measurement Science and Technology, 14:1117–1122, 2003.110
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CHAPTER 7. CONCLUSION AND FUTURE WORK 109each sensor. The proposed set theoretic framework can be used to actively adaptindividual sensor weights in accordance with the feedback from an oracle.
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