In Dempster-Shafer theory, belief functions induced by distinct pieces of evidence can be combined by Dempster's rule of combination. The concept of distinctness has not been formally defined. We present a tentative definition of the concept of distinctness and compare this definition with the definition of stochastic independence described in probability theory.

This paper aims at providing a preliminary discussion on how to deal with spatio-temporal information in the context of behaviour recognition. It draws comparison with how humans reason in other areas, such as law, and discusses some of the pros and cons of formalisms for handling uncertainty, starting with probability theory, continuing with the Dempster-Shafer theory, and concluding with fuzz...

Recently, Hummel and Landy proposed a variation on the Dempster/Shafer theory of evidence that tracks only the first and second order statistics of the opinions of sets of experts. This extension permits the tracking of statistics of probabilistic opinions, however, as opposed to tracking merely Boolean opinions (or possibilities within the "frame of discernment"). Both the Dempster/Shafer form...

Dempster-Shafer evidence theory (D-S) is an effective instrument for merging the collected pieces of basic probability assignment (BPA), and it exhibits superiority in achieving robustness soft computing decision making uncertain imprecise environment. However, determination BPA still uncertain, merely applying can sometimes lead to counterintuitive results when lines conflict. In this paper, a...

Lymphoma detection and segmentation from whole-body Positron Emission Tomography/Computed Tomography (PET/CT) volumes are crucial for surgical indication radiotherapy. Designing automatic methods capable of effectively exploiting the information PET CT as well resolving their uncertainty remain a challenge. In this paper, we propose an lymphoma model using UNet with evidential PET/CT fusion lay...