In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level.
From this study, we can conclude first that the classification of uterine EMG signals can be improved by applying a decision-level data fusion rule.
While the ranking of Wang and Luo (2009) was not affected by the decision level, the proposed method revealed that this ranking order is valid for a low-level decision, i.e., (alpha le 0.5).
This new approach will be achieved by implementing a new hierarchical decision level implemented in a remote location, using high-tech products and technologies along with new algorithms and strategies.
The larviciding decision process, as described by the respondents was shorter, appears to have been started by a decision at the highest levels of government and circumvented a number of policy processes and actors that are reflected in the normal processes of vector control policymaking.
Herein, the data fusion is done at the decision level by using a weighted majority voting (WMV) rule.
The dissimilarity measure of each region are fused at the decision level by exploring 1-out-of-n: Accept (A) post-classifier in order to reduce the false rejection rate.
By contrast, fusing data sources at decision level, such as in the ensemble learning framework, is considered as an intuitive manner to deal with heterogeneous data.
These individuals were thus the poorest individuals in a context, as described by a decision-maker, where "the level of poverty is quite high and therefore the question of resources [to support healthcare access] is sensitive".
In the current B-MC-ELM-AE-TsEL framework, the B-MC-ELM-AE features are integrated by a classifier- or decision-level fusion method, that is to say, ensemble learning can be applied to all the classification results of individual column of B-ELM-AE.
