Abstract: The Functions of Multiple Instances (FUMI) method for learning target pattern and non-target patterns is introduced and extended. The FUMI method differs significantly from traditional supervised learning algorithms because only functions of target patterns are available. Moreover, these functions… Read More
Tag: target detection
Multiclass subpixel target detection using functions of multiple instances
Abstract: The Multi-class Convex-FUMI (Multi-class C-FUMI) method is developed and described. The method is capable of learning prototypes for multiple target classes from hyperspectral imagery. Multi-class C-FUMI is a non-traditional supervised learning method based on the Functions of Multiple Instances… Read More
Pattern recognition using functions of multiple instances
Abstract: The Functions of Multiple Instances (FUMI) method for learning a target prototype from data points that are functions of target and non-target prototypes is introduced. In this paper, a specific case is considered where, given data points which are… Read More
Quantifying the benefit of airborne and ground sensor fusion for target detection
Abstract: In this paper, a study involving the detection of buried objects by fusing airborne Multi-Spectral Imagery (MSI) and ground-based Ground Penetrating Radar (GPR) data is investigated. The benefit of using the airborne sensor to cue the GPR, which will… Read More
Vegetation mapping for landmine detection using long-wave hyperspectral imagery
Abstract: We develop a vegetation mapping method using long-wave hyperspectral imagery and apply it to landmine detection. The novel aspect of the method is that it makes use of emissivity skewness. The main purpose of vegetation detection for mine detection… Read More