Abstract: In classifier (or regression) fusion the aim is to combine the outputs of several algorithms to boost overall performance. Standard supervised fusion algorithms often require accurate and precise training labels. However, accurate labels may be difficult to obtain in… Read More
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Target Concept Learning From Ambiguously Labeled Data
Abstract: The multiple instance learning problem addresses the case where training data comes with label ambiguity, i.e., the learner has access only to inaccurately labeled data. For example, in target detection from remotely sensed hyperspectral imagery, targets are usually sub-pixel… Read More
Multiple Instance Choquet Integral For MultiResolution Sensor Fusion
Abstract: Imagine you are traveling to Columbia,MO for the first time. On your flight to Columbia, the woman sitting next to you recommended a bakery by a large park with a big yellow umbrella outside. After you land, you need… Read More
Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection
Abstract: The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented. In many hyperspectral target detection problems, acquiring accurately labeled training data is difficult. Furthermore, each pixel containing target is likely to be a… Read More
Possibilistic Fuzzy Local Information C-Means for Sonar Image Segmentation
Abstract: Side-look synthetic aperture sonar (SAS) can produce very high quality images of the sea-floor. When viewing this imagery, a human observer can often easily identify various sea-floor textures such as sand ripple, hard-packed sand, sea grass and rock. In… Read More
Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring from Ballistocardiograms
Abstract: A multiple instance dictionary learning approach, Dictionary Learning using Functions of Multiple Instances (DLFUMI), is used to perform beat-to-beat heart rate estimation and to characterize heartbeat signatures from ballistocardiogram (BCG) signals collected with a hydraulic bed sensor. DL-FUMI estimates… Read More
Measures of the Shapley index for learning lower complexity fuzzy integrals
Abstract: The fuzzy integral (FI) is used frequently as a parametric nonlinear aggregation operator for data or information fusion. To date, numerous data-driven algorithms have been put forth to learn the FI for tasks like signal and image processing, multi-criteria… Read More
Aggregation of Choquet integrals in GPR and EMI for handheld platform-based explosive hazard detection
Abstract: Substantial interest resides in identifying sensors, algorithms and fusion theories to detect buried explosive hazards. This is a significant research effort because it impacts the safety and lives of civilians and soldiers alike. Herein, we explore the fusion of… Read More
LBP Features for Hand-Held Ground Penetrating Radar
Abstract: Ground penetrating radar (GPR) has the ability to detect buried targets with little or no metal content. Achieving superior detection performance with a hand-held GPR can be very challenging due to the quality of the data, inconsistency of target… Read More
Fourier Features for Explosive Hazard Detection using a Wideband Electromagnetic Induction Sensor
Abstract: Sensors which use electromagnetic induction (EMI) to excite a response in conducting bodies have been investigated for the purpose of detecting buried explosives. In particular, wide band EMI sensors which use a relatively low number of operating frequencies have… Read More