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We then reconstruct the full image using the weighted fusion of these four subspace images.
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When we use the weighted fusion penalty in addition to the lasso penalty as in GcFlasso, GwFlasso and GwFlasso, the performance significantly improves over lasso across all of the samples sizes shown in Figure 3.
The outputs of the two classifiers are consolidated into a single vector of scores using the weighted sum rule of fusion.
Then they were optimized using the weighted property index method.
Finally, according to the weighted fusion strategy, we realize the effective utilization of bootstrapped observations.
Q is the fusion quality index, Q W is the weighted fusion quality index, and Q E is the edge-dependent fusion quality index.
In addition, further improved features are more developed by the weighted fusion of five local regions.
For results combinations, we use the weighted Z-method [17].
All analyses used the weighted scores.
The information fusion state prediction is obtained by using the information fusion formulae [13, 23].
Then local estimates are transmitted to the fusion center over a perfect connection, where a distributed fusion filter is obtained by using the well-known matrix-weighted fusion estimation algorithm in the linear minimum variance sense.
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