This paper proposes a probabilistic robust hyperbola mixture model based on a
classification expectation maximization algorithm and applies this algorithm to Ground …

Active learning is showing to be a useful approach to improve the efficiency of the
classification process for remote sensing images. This letter introduces a new active …

A technique for making landmine detection with a ground-penetrating radar (GPR) sensor
more robust to fluctuations in environmental conditions is presented. Context-dependent …

This paper proposes a probabilistic conic mixture model based on a classification
expectation maximization algorithm and applies this algorithm to Ground Penetrating Radar …

In this paper, a new method is proposed to identify and classify the data obtained by the
sensor network (SN) for the detection of mines. This method is used for the identification of …

Due to the complexity of the medium composition, physical characteristics and the spreading
of electromagnetic waves, the extraction and automatic target detection of the Ground …

The detection of embedded object from ground penetrating radar GPR imagery is our goal.
The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic …

In this work, we present a new support vector machine (SVM)-based active learning method
for the classification of remote sensing images. Starting from an initial suboptimal training …

Context-dependent classification techniques applied to landmine detection with ground-
penetrating radar (GPR) have demonstrated substantial performance improvements over …

The detection of embedded object from ground penetrating radar GPR imagery is our goal.
The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic …