The multiview opinions are automatically fused sequentially, two opinions at a time, to capture how live experimental data will be presented to the CNN. Opinions from the first two different views are fused with uncertainty as outlined above. After that, a fused opinion is formed, which is then fused with the third opinion, and so on. During the opinion fusion, uncertainties are also fused. This process stops when the uncertainty is below a desired threshold. The Dempster-Shafer theory implies the following properties that are appropriate for decision making. First, when fused with each new opinion, the uncertainty mass successively decreases, indicating an increasing confidence in decision making, ensuring that the procedure automatically stops analyzing new DPs when enough evidence is accumulated. Second, when two uncertainties are high, the fused uncertainty remain high. For this reason, only the opinions with high confidence (low uncertainty) play a significant role in the decisionmaking process. Third, the accuracy can be improved during opinion fusion; this is true when the belief mass of the correct class in the new opinion is higher than the maximum belief mass in the previous opinion. Although the accuracy can decrease when fused with a wrong prediction, the amount of degradation is limited when the uncertainty associated with the wrong prediction is large.