… the usefulness of information fusion. A comprehensive list of … to a particular decision-level
integration scenario where … system design for decision-level classifier fusion that uses the …

… Though the term ‘decision level fusion’ has appeared widely in … an information fusion strategy,
decision level fusion also has … data fusion (Hall & Llinas, 1997), multispectral image fusion …

… Fusion is a popular practice to increase the reliability of … fusion scheme at decision level
by the AND or OR rule, based on optimizing matching score thresholds. The proposed fusion …

… , or hybrid fusion. Decision-level fusion involves fusion of sensor information that is preliminary
determinated by the sensors. Examples of decisionlevel fusion methods include weighted …

… For the decision-level fusion, we need to obtain the probability of each supervoxel instead
of the color values of the original VCCS method. K-means clustering is used to generate the …

… GPR and EMI sensors were fused using several decision-level fusion approaches. Brusmark
et al. [4] demonstrated the decision-level fusion of coincidently sampled GPR and EMI …

… most of the literature in decision level fusion. We are more … be asserted before any decision
level fusion takes place. The … methods applied for decision level fusion in remote sensing. …

… We propose a novel sensor fusion technique at the decision level that looks at targets as …
the proposed technique can outperform existing fusion techniques on the decision level. …

… Final step is the concluding fusion process. In the information processing architecture, the
peak of the fusion level is the decision-level fusion, also known as high-level fusion. People …

… We propose a robust decision-level fusion … -fusion is not used to predict/classify the
pandemic (see Table 1). Therefore, in the current study, we propose a robust decision-level fusion …