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We present a novel method for fusing the decisions of multiple classification algorithms which use different features, classification methods, ...
We present a novel method for fusing the decisions of multiple classification algorithms which use different features, classification methods, ...
We present a novel method for fusing the decisions of multiple classification algorithms which use different fea- tures, classification methods, and data ...
We present a novel method for fusing the decisions of multiple classification algorithms which use different features, classification methods, ...
Context-Dependent Fusion of Multiple Algorithms with Minimum ...
colab.ws › articles › icmla.2009.119
Context-Dependent Fusion of Multiple Algorithms with Minimum Classification Error Learning. Zhang L., Frigui H., Gader P.
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We present a method for fusing the decisions of multiple algorithms that use different hyperspectral imagery (HI) classification methods and apply it to ...
This Doctoral Dissertation is brought to you for free and open access by ThinkIR: The University of Louisville's. Institutional Repository.
Combining classifiers aims at exploiting this complementary information that seems to reside in the various classifiers. This is illustrated in Figure 4.29.
The training part of CDF has two main components: context extraction and algorithm fusion. ... These methods use automated learning and classification algorithms ...
Feb 3, 2014 · Multi-sensor information fusion for state estimation is a well studied problem in robotics, with many applica- tions and well known benefits ...