Fire Detection Algorithms Using Multimodal ... - Bilkent University

BIBLIOGRAPHY 117[67] L. Rabiner and B.-H. Juang. Fundamentals of Speech Recognition. Prentice-Hall Inc., 1993.[68] A. Rahman and M. Murshed. Real-time temporal texture characterisationusing block-based motion co-occurrence statistics. In Proceedings of theIEEE International Conference on Image Processing (ICIP), pages 1593–1596, 2004.[69] D. Reynolds and R. Rose. Robust text-independent speaker identificationusing gaussian mixture speaker models. IEEE Transactions on Speech andAudio Processing, 3(1):72–83, 1995.[70] Y. Sahin. Animals as mobile biological sensors for forest fire detection. Sensors,7(12):3084–3099, 2007.[71] P. Saisan, G. Doretto, Y. Wu, and S. Soatto. Dynamic texture recognition.In Proceedings of the IEEE Conference on Computer Vision and PatternRecognition (CVPR), volume 2, pages 58–63, December 2001.[72] J. Schlimmer and R. Granger. Incremental learning from noisy data. MachineLearning, 1, page 317354, 1986.[73] B. Schnaufer and W. Jenkins. New data-reusing LMS algorithms for improvedconvergence. In Proceedings of the Asilomar Conference, PacificGroves, CA, pages 1584–1588, 1993.[74] A. Singer and M. Feder. Universal linear prediction by model order weighting.IEEE Transactions on Signal Processing, 47-10:2685–2699, 1999.[75] J. Smith, C.-Y. Lin, and M. Naphade. Video texture indexing using spatiotemporalwavelets. In Proceedings of the IEEE International Conferenceon Image Processing (ICIP), volume 2, pages 437–440, 2002.[76] L. St-Laurent, D. Prvost, and X. Maldague. Thermal imaging for enhancedforeground-background segmentation. In Proceedings of the 8-th InternationalConference on Quantitative InfraRed Thermography, 2006.