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To efficiently analyze the data, a new metric for assessment of data utility, the combined classification quality measure, was developed.
For the percentage distribution of visual fields, the repeats and unreliable fields were excluded, leaving 894 fields.The intergrader agreement of this combined classification system was a κ value of 0.61 (95% CI 0.59 to 0.63).
In the first of the discussed models the potential for combined classification improvement by GA-selected weights for the soft combining of classifier outputs has been investigated.
It is concluded that the combined classification method together with the object-based change detection analysis leads to an improved classification accuracy and land cover change detection.
This type-2 fusion architecture takes considerations of the classification results from individual SVMs classifiers and generates the combined classification decision as the output.
Choosing a single discrete value for the combined classification presents a loss of information.
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These combined classifications then form the input for a change detection analysis between the two dates by applying post-classification, object-based change analysis using image differencing.
No meta-analyses were possible exclusively on a whiplash associated disorder II population, as most trials included combined classifications of whiplash associated disorders in their populations.
The new model, however, combines classification of steady states with transient evaluation via time series analysis.
However, in the literature, there is no generic hierarchical approach for estimation and no hybrid based solution that combines classification and estimation techniques hierarchically.
IDNet is the first system that exploits a deep learning approach as universal feature extractors for gait recognition, and that combines classification results from subsequent walking cycles into a multi-stage decision making framework.
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