Nada Milisavljevic

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—A two-level approach for modeling and fusion of anti-personnel mine detection sensors in terms of belief functions within the Dempster–Shafer framework is presented. Three promising and complementary sensors are considered: a metal detector, an infrared camera, and a ground-penetrating radar. Since the metal detector, the most often used mine detection(More)
A method for modeling and combination of measures extracted from a ground-penetrating radar (GPR) in terms of belief functions within the Dempster–Shafer framework is presented and illustrated on a real GPR data set. A starting point in the analysis is a preprocessed C-scan of a sand-lane containing some mines and false alarms. In order to improve the(More)
—The detection of antipersonnel landmines using ground-penetrating radar (GPR) is particularly hindered by the predominant soil surface and antenna reflections. In this paper, we propose a novel approach to filter out these effects from 2-D off-ground monostatic GPR data by adapting and combining the radar antenna subsurface model of Lambot et al. with(More)
—Two approaches for combining humanitarian mine detection sensors are presented—one based on belief functions and the other one based on possibility theory. The approaches are described in parallel. First, different measures are extracted from the sensor data. Mass functions and possibility distributions are then derived from the measures based on prior(More)
The aim of the approach proposed in this paper is to determine a potential crop extent prior to the crop season, by determining regions that might change in time vs. those that surely do not change. We use multi-annual PALSAR-1 data since in dry conditions, L-band HH/HV data have a potential of distinguishing between bare soil and other classes. In(More)
—We propose a method for combining humanitarian mine detection sensors based on possibility theory. Firstly, different features are extracted from the sensor data. Possibility distributions are then derived from the features based on prior information. After that, the combination of possibility degrees is performed in two steps, on separate sensor level and(More)