Publications
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Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest Ghent University
Combining feature fusion and decision fusion for classification of hyperspectral and LiDAR data Ghent University
This paper proposes a method to combine feature fusion and decision fusion together for multi-sensor data classification. First, morphological features which contain elevation and spatial information, are generated on both LiDAR data and the first few principal components (PCs) of original hyperspectral (HS) image. We got the fused features by projecting the spectral (original HS image), spatial and elevation features onto a lower subspace ...
Geometry of nuclear fusion diagnostic data on information manifolds with an application to fusion plasma confinement Ghent University
Pattern recognition is becoming an increasingly important tool for making inferences from the massive amounts of data produced in fusion experiments. The purpose is to contribute to physics studies and plasma control. In this work, we address the visualization of plasma confinement data and their dynamics, the identification of confinement regimes and the establishment of a scaling law for the energy confinement time. We take an intrinsically ...
Remote sensing data fusion : guided filter-based hyperspectral pansharpening and graph-based feature-level fusion Ghent University
A novel data fusion method for the effective analysis of multiple panels of flow cytometry data Hasselt University
Multicolour flow cytometry (MFC) is used to measure multiple cellular markers at the single-cell level. Cellular markers may be coloured with different panels of fluorescently-labelled antibodies to enable cell identification or the detection of activated cells in pre-defined, gated’ specific cell subsets. The number of markers that can be used per measurement is technologically limited however, requiring every panel to be analysed in a separate ...
Manifold Learning for Visualization, Prioritization, and Data Fusion of Mass Spectrometry Imaging Data KU Leuven
Mass Spectrometry Imaging (MSI) is a powerful molecular imaging technology that can detect the spatial distribution of molecules in a tissue section. Because MSI does not require any a priori labeling, the technique has become very popular for the explorative comparison of metabolites, lipids, peptides and proteins between various tissue regions. Since it has been shown that tumor heterogeneity plays an important role in tumor biology, it has ...
Tensor decompositions and data fusion in epileptic EEG and fMRI data KU Leuven
© 2016 The Authors. WIREs Data Mining and Knowledge Discovery published by John Wiley & Sons, Ltd. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) record a mixture of ongoing neural processes, physiological and nonphysiological noise. The pattern of interest, such as epileptic activity, is often hidden within this noisy mixture. Therefore, blind source separation (BSS) techniques, which can retrieve the activity ...
Feature fusion of hyperspectral and LiDAR data for classification of remote sensing data from urban area Ghent University
Joint probabilistic data fusion for pedestrian detection in multimodal images Ghent University
Pedestrian detection systems are one of the emerging technologies due to their wide range of applications. However, due to the dynamic environments, the data obtained from a single visual sensor for these operations is not sufficient to cover all the environmental conditions, such as varying natural light, weather conditions, etc. Therefore, the use of multiple heterogeneous visual sensors for such systems is indispensable. However, this ...