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The analysis was also performed without reconstruction by combining the model results from projection images using Bayesian decision fusion algorithm.
Figure 11 shows that rule-based decision fusion algorithm is the worst method of emotion recognition tested in our data.
The local vote decision fusion algorithm, where sensors correct their decisions about the target's presence or absence using decisions of neighboring sensors, and then makes a collective decision, is proposed in [3].
To do so, we propose a Bayesian decision fusion algorithm, BCmicrO.
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Clustering-based decision fusion algorithms and fusion rules for distributed target detection in WSNs were studied in [14 16].
When training the decision fusion algorithms, a set of predictions for each individual decoder is required.
To avoid this, a second dataset for fusion training was generated separately for the decision fusion algorithms.
In order to demonstrate the effects of artifacts on classifier performance, a series of classification experiments are designed using a multi-channel decision fusion classification algorithm.
This study addressed the classification of multi-temporal satellite data from RapidEye by considering different classifier algorithms and decision fusion.
In this report, we examine two algorithms for decision fusion of continuous variables: the Kalman filter and artificial neural networks (ANNs).
During the decision fusion, the reliability of each base classifier algorithm was considered to exclude less reliable inputs at the class-basis.
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