Map matching is not always perfect and sometimes produces mismatches. Thus, there is a degree of uncertainty for how well a map-matching algorithm will perform under certain circumstances. Circumstantial factors include accuracies of sensor data and surrounding road network structure, among others. This paper attempts to shed light on this uncertainty and proposes a methodology for predicting p...

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical under constraints. Symmetry-based feature extraction representation neural networks may unravel the most informative contents large image databases. Despite significant achievements artificial intelligence recognition classification regular patterns, problem uncertainty ...

One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...

This paper presents an approach to capturing and representing the uncertainty inherent in any attempt to classify continuously varying geographical phenomena into discrete categories. This uncertainty is captured during a visual photo-interpretation and a computerised image classiŽ cation process and encoded as a series of fuzzy surfaces. These store the fuzzy membership values (FMVs) of each l...

The complexity of land use and land cover change (LULC) models is often attributed to spatial heterogeneity of the phenomena they try to emulate. The associated outcome uncertainty stems from a combination of model unknowns. Contrarily to the widely shared consensus on the importance of evaluating outcome uncertainty, little attention has been given to the role a well-structured spatially-expli...

subject to some impulses at certain points. Our work was inspired by a paper by Capietto–Mawhin–Zanolin [1], where the case of no impulses was treated. The major difference between paper [1] and ours is that instead of topological degree, we use the elementary method based on essential maps. In this context, we also give some new contributions to Granas’ theory of continuation principles. The f...

The accuracy assessment of land cover maps is traditionally based on reference sample observations randomly selected over the study area. It is assumed that reference sample observations, representing the “real” land cover at Earth’s surface, are free of errors. However, some of these may be erroneous. These errors are sometimes due to an uncertainty in the identification of the most adequate r...

We present a novel multi-modal fusion framework for nonsequential person detection, localization and identification from multiple views. Our goal is independent processing of randomly-accessed sections of video, either individual frames or small batches thereof. This way, we aim to limit the error propagation that makes the existing approaches unsuitable for fully-autonomous tracking of multipl...