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A novel approach is presented in order to reject correspondence outliers between frames using the parallax-based rigidity constraint for epipolar geometry estimation. In this approach, the invariance of 3-D relative projective structure of a stationary sce ...
Based on weak lensing data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), in this paper we study the mass-concentration (M-c) relation for similar to 200 redMaPPer clusters in the fields. We extract the M-c relation by measuring the den ...
Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...
This paper deals with the resolution of inverse problems in a periodic setting or, in other terms, the reconstruction of periodic continuous-domain signals from their noisy measurements. We focus on two reconstruction paradigms: variational and statistical ...
The recently developed traffic signal control strategy known as traffic-responsive urban control (TUC) requires availability of a fixed signal plan that is sufficiently efficient under undersaturated traffic conditions. To drop this requirement, the well-k ...
In this work, we derive a near-optimal combination rule for adaptation over networks. To do so, we first establish a useful result pertaining to the steady-state distribution of the estimator of an LMS filter. Specifically, under small step-sizes and some ...
Tailoring solid surfaces attracts a number of technological and scientific interest with numerous applications. One method to modify a solid surface is via the formation of a molecular film. The adsorbed molecules assemble spontaneously (self assemble) for ...
Information theory has been used as an organizing principle in neuroscience for several decades. Estimates of the mutual information (MI) between signals acquired in neurophysiological experiments are believed to yield insights into the structure of the un ...
Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...
This thesis focuses on the decisional process of autonomous systems, and more particularly, on the way to take a decision when the time at disposal in order to assess the whole situation is shorter than necessary. Indeed, numerous systems propose solutions ...
