Zobrazeno 1 - 10 of 24 pro vyhledávání: '"Adnet, Claude"'
1
Report
Near out-of-distribution detection for low-resolution radar micro-Doppler signatures
Autor: Bauw, Martin, Velasco-Forero, Santiago, Angulo, Jesus, Adnet, Claude, Airiau, Olivier
Near out-of-distribution detection (OODD) aims at discriminating semantically similar data points without the supervision required for classification. This paper puts forward an OODD use case for radar targets detection extensible to other kinds of s
Externí odkaz: http://arxiv.org/abs/2205.07869
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2
Report
From Unsupervised to Semi-supervised Anomaly Detection Methods for HRRP Targets
Autor: Bauw, Martin, Velasco-Forero, Santiago, Angulo, Jesus, Adnet, Claude, Airiau, Olivier
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. This work aims at presenting a benchmark gathering common and recently
Externí odkaz: http://arxiv.org/abs/2106.11168
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3
Report
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection
Autor: Bauw, Martin, Velasco-Forero, Santiago, Angulo, Jesus, Adnet, Claude, Airiau, Olivier
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 work, the original random projection outlyingness measure is modified
Externí odkaz: http://arxiv.org/abs/2106.15307
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4
Report
Regularized maximum likelihood estimation of covariance matrices of elliptical distributions
Autor: Culan, Christophe, Adnet, Claude
The maximum likelihood principle is widely used in statistics, and the associated estimators often display good properties. indeed maximum likelihood estimators are guaranteed to be asymptotically efficient under mild conditions. However in some sett
Externí odkaz: http://arxiv.org/abs/1611.10266
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5
Report
Partial estimators and application to covariance estimation of gaussian and elliptical distributions
Autor: Culan, Christophe, Adnet, Claude
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 applied contexts because of their sensitivity to outliers. Of particul
Externí odkaz: http://arxiv.org/abs/1611.07418
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6
Report
Maximum likelihood estimation of covariances of elliptically symmetric distributions
Autor: Culan, Christophe, Adnet, Claude
Elliptically symmetric distributions are widely used in portfolio modeling, as well as in signal processing applications for modeling impulsive background noises. Of particular interest are algorithms for covariance estimation and subspace detection
Externí odkaz: http://arxiv.org/abs/1611.04365
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8
Conference
Extract before detect, coherent extraction based on gridless Compressed Sensing.
Autor: Desodt, Guy, Adnet, Claude, Martin, Aurelie, Castaing, Richard
Publikováno v: 2015 3rd International Workshop on Compressed Sensing Theory & its Applications to Radar, Sonar & Remote Sensing (CoSeRa); 2015, p174-178, 5p
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