3 citations · 6 across the 6 of their papers we have counts for
6 papers
Near out-of-distribution detection for low-resolution radar micro-Doppler signatures
Martin Bauw, Santiago Velasco-Forero, Jesus Angulo +2
Near out-of-distribution detection (OODD) aims at discriminating semantically similar data points without the supervision required for classification. This paper puts forward an OO…
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection
Martin Bauw, Santiago Velasco-Forero, Jesus Angulo +2
Random projection is a common technique for designing algorithms in a variety of areas, including information retrieval, compressive sensing and measuring of outlyingness. In this…
From Unsupervised to Semi-supervised Anomaly Detection Methods for HRRP Targets
Martin Bauw, Santiago Velasco-Forero, Jesus Angulo +2
Responding to the challenge of detecting unusual radar targets in a well identified environment, innovative anomaly and novelty detection methods keep emerging in the literature. T…
Regularized maximum likelihood estimation of covariance matrices of elliptical distributions
Christophe Culan, Claude Adnet
The maximum likelihood principle is widely used in statistics, and the associated estimators often display good properties. indeed maximum likelihood estimators are guaranteed to b…
Partial estimators and application to covariance estimation of gaussian and elliptical distributions
Christophe Culan, Claude Adnet
Robustness to outliers is often a desirable property of statistical estimators. Indeed many well known estimators offer very good optimal performance in theory but are unusable in…
Maximum likelihood estimation of covariances of elliptically symmetric distributions
Christophe Culan, Claude Adnet
Elliptically symmetric distributions are widely used in portfolio modeling, as well as in signal processing applications for modeling impulsive background noises. Of particular int…