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Ensemble classifiers are known to generally perform better than each individual classifier of which they consist. One approach to classifier fusion is to apply Shaferpsilas theory of evidence. While most approaches have adopted Dempsterpsilas rule of combination, a multitude of combination rules have been proposed. A number of combination rules as well as two voting rules are compared when used in...
This paper introduces a generic architecture for the fusion of perceptual processes and its application in real-time object tracking. In this architecture, the well known anchoring approach is, by integrating techniques from information fusion, extended to multi-modal anchoring so as to be applicable in a multi-process environment. The system architecture is designed to be applicable in a generic...
In the sensor-based applications context, sensor reliability is not always taken into account. Due to the uncertain nature of sensors, we must integrate to the problem of belief attached to the sensors data. This paper deals with the dysfunction detection based on a two-level approach. The first level extracts conflict information of the combination of multiple data sources. The second level is based...
Tracking algorithms are often designed around optimistic assumptions on uncertainty model. Handling with conflicting data, however, requires specific strategies, that consider quality of information sources. To improve performance of tracking systems, the use of reliability, as evaluation of quality of data sources, has been proved to be a promising technique. In this paper we show how to use reliability...
Todaypsilas military and humanitarian operations involve multiple partners and agencies and rely on information culled from a variety of different sources, including humans, sensors, robots, etc. Efficient, timely exchange and evaluation of information is required for effective operations. However, the sheer volume of information prohibits integration of incoming information for the situation awareness...
This document describes what particular pieces of information about source should be taken into account to get a reasonable assessment of an attribute information retrieved based on the sensor data or human originated information. It has been proven that actual sensor weights and hypotheses masses do not change randomly, but they vary in time according to tracked target motion, however not directly...
Recent cyber security research has focused on providing a situation awareness of computer networks by identifying incoming attacks. FuSIA: Future Situation and Impact Awareness seeks to extend this situation awareness via estimating plausible futures of ongoing attacks. Plausible futures, derived based on current progress of attacks, are projected situations that computer security analysts may use...
In the belief function theory, the concept of conflict appearing while confronting several expertspsila opinions can serve for many purposes, and in particular it can be used as an indicator of the relative reliability of the experts. The traditional definition of conflict as the basic belief assigned to the empty set during the combination has several issues and in particular it may not adequately...
This work deals with the problem of the fault-tolerant estimation of discrete-time stochastic processes. A random walk process is estimated from the fusion of measurement uncertainty intervals provided by a set of sensors. Two algorithms of interval propagation and contraction are proposed. For both algorithms, interval contraction is done using fault-tolerant interval functions rather than the non-robust...
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