Entropy-Functional-Based Online Adaptive Decision Fusion Framework With Application to Wildfire Detection in Video

In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a rea...

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Veröffentlicht in:	IEEE transactions on image processing 2012-05, Vol.21 (5), p.2853-2865
Hauptverfasser:	Gunay, O., Toreyin, B. U., Kose, K., Cetin, A. E.
Format:	Artikel
Sprache:	eng
Schlagworte:	Active learning Algorithms Applied sciences Approximation algorithms Artificial Intelligence Compounds Computer science control theory systems Computer vision Confidence intervals decision fusion Disasters - classification Entropy entropy maximization Equations Exact sciences and technology Feedback Fires Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Information theory Information, signal and communications theory On-line systems Online online learning Online Systems Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Photography - methods projections onto convex sets Reproducibility of Results Security Sensitivity and Specificity Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Studies Subtraction Technique Telecommunications and information theory Vectors Video Recording - methods wildfire detection using video Wildfires
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