Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Mian, Ammar"'
In this paper, a new classification model based on covariance matrices is built in order to classify buried objects. The inputs of the proposed models are the hyperbola thumbnails obtained with a classical Ground Penetrating Radar (GPR) system. These
Externí odkaz:
http://arxiv.org/abs/2410.07117
In this study, we consider the realm of covariance matrices in machine learning, particularly focusing on computing Fr\'echet means on the manifold of symmetric positive definite matrices, commonly referred to as Karcher or geometric means. Such mean
Externí odkaz:
http://arxiv.org/abs/2405.06558
We develop the information geometry of scaled Gaussian distributions for which the covariance matrix exhibits a Kronecker product structure. This model and its geometry are then used to propose an online change detection (CD) algorithm for multivaria
Externí odkaz:
http://arxiv.org/abs/2312.02807
Multi-array systems are widely used in sonar and radar applications. They can improve communication speeds, target discrimination, and imaging. In the case of a multibeam sonar system that can operate two receiving arrays, we derive new adaptive to i
Externí odkaz:
http://arxiv.org/abs/2303.17979
Graphical models and factor analysis are well-established tools in multivariate statistics. While these models can be both linked to structures exhibited by covariance and precision matrices, they are generally not jointly leveraged within graph lear
Externí odkaz:
http://arxiv.org/abs/2210.11950
Publikováno v:
In Signal Processing November 2024 224
This paper proposes a strategy to handle missing data for the classification of electroencephalograms using covariance matrices. It relies on the observed-data likelihood within an expectation-maximization algorithm. This approach is compared to two
Externí odkaz:
http://arxiv.org/abs/2110.10011
Autor:
Mian, Ammar
La télédétection par Radar à Synthèse d’Ouverture (RSO) offre une opportunité unique d’enregistrer, d’analyser et de prédire l’évolution de la surface de la Terre. La dernière décennie a permis l’avènement de nombreuses missions
Externí odkaz:
http://www.theses.fr/2019SACLC074/document
Autor:
Ollila, Esa, Mian, Ammar
Huber's criterion can be used for robust joint estimation of regression and scale parameters in the linear model. Huber's (Huber, 1981) motivation for introducing the criterion stemmed from non-convexity of the joint maximum likelihood objective func
Externí odkaz:
http://arxiv.org/abs/2008.10982
Autor:
Bouchard, Florent, Mian, Ammar, Zhou, Jialun, Said, Salem, Ginolhac, Guillaume, Berthoumieu, Yannick
A new Riemannian geometry for the Compound Gaussian distribution is proposed. In particular, the Fisher information metric is obtained, along with corresponding geodesics and distance function. This new geometry is applied on a change detection probl
Externí odkaz:
http://arxiv.org/abs/2005.10087