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Matching the TALIS and PISA surveys for each of these 24 countries is beyond the scope of the current study, however the potential for data fusion to provide complete information on multiple countries is promising.
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Concrete results are: (1) adaptive weighted fusion algorithm for data fusion computing.
For data fusion, the watershed image processing technique was used.
Therefore, their average is a good option for data fusion.
The basic procedure that has been developed for the fusion process is shown in algorithmic form as described below: The basic procedure for data fusion: for x = 1 n.
For data fusion, so-called mid-level data fusion architecture was used [ 21].
This equally true for the inclusion of other sources of information like author names or journal name and for the investigation into potential data fusion methods relying on both RF and NB.
The results of these measurements show the high potential of reconstruction and data fusion for the improvement and simplification of the interpretability of large data sets measured with impulse-echo methods.
We highlight potential benefits of multisensor data fusion, challenges in realizing those benefits, and opportunities for further improvement.
Recently, a maximum-likelihood estimation (MLE) approach was proposed for multisensory data fusion in human [7].
The quest for suitable data fusion schemes, which could ideally optimize the exploitation of the information residing in composite datasets, is an emergent area with numerous potential applications.
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