Concept

Multiplication algorithm

Related publications (142)

Robust algorithm for aligning two-dimensional chromatograms

Jeremy Samuel Arey, Jonas Gros, Petros Dimitriou Christidis, Rebecca Rutler, Deedar Nabi

Comprehensive, two-dimensional gas chromatography (GC x GC) chromatogram's typically exhibit run-to-run retention time variability. Chromatogram alignment is often a desirable step prior to further analysis of the data, for example, in studies of environme ...

Amer Chemical Soc2012

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

Institute of Physics2011

Multilevel Schwarz methods for elliptic partial differential equations

Alfio Quarteroni, Giovanni Migliorati

We investigate multilevel Schwarz domain decomposition preconditioners, to efficiently solve linear systems arising from numerical discretizations of elliptic partial differential equations by the finite element method. In our analysis we deal with unstruc ...

Elsevier2011

Detection and Recovery From Pollution Attacks in Coding Based Distributed Storage Schemes

László Czap, Levente Buttyan

We address the problem of pollution attacks in coding based distributed storage systems. In a pollution attack, the adversary maliciously alters some of the stored encoded packets, which results in the incorrect decoding of a large part of the original dat ...

Institute of Electrical and Electronics Engineers2011

On Improving Face Detection Performance by Modelling Contextual Information

Sébastien Marcel, Cosmin Atanasoaei

In this paper we present a new method to enhance object detection by removing false alarms and merging multiple detections in a principled way with few parameters. The method models the output of an object classiï¬er which we consider as the context. A hie ...

Idiap2010

An optimal first-order solver for the TV-$L_1$ optical flow problem

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo

In this study, we address the problem of computing efficiently a dense optical flow between two images under a total variation (TV) regularization and an

L_1

norm data fidelity constraint using a variational method. We build upon Nesterov's framework for ...

2010

Diffusion LMS Strategies for Distributed Estimation

Ali H. Sayed

We consider the problem of distributed estimation, where a set of nodes is required to collectively estimate some parameter of interest from noisy measurements. The problem is useful in several contexts including wireless and sensor networks, where scalabi ...

IEEE2010

Fast Interscale Wavelet Denoising of Poisson-Corrupted Images

Michaël Unser, Thierry Blu, Cédric René Jean Vonesch, Florian Luisier

We present a fast algorithm for image restoration in the presence of Poisson noise. Our approach is based on (1) the minimization of an unbiased estimate of the MSE for Poisson noise, (2) a linear parametrization of the denoising process and (3) the preser ...

Elsevier2010

Fast Detection Of Cells Using A Continuously Scalable Mexican-Hat-Like Template

Michaël Unser, Daniel Sage, Kunal Narayan Chaudhury

We propose a fast algorithm for the detection of cells in fluorescence images. The algorithm, which estimates the number of cells and their respective centers and radii, relies on the fast computation of intensity-based correlations between the cells and a ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Fast Detection of Cells Using a Continuously Scalable Mexican-Hat-Like Template

Michaël Unser, Daniel Sage, Zsuzsanna Püspöki, Kunal Narayan Chaudhury

IEEE2010

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An optimal first-order solver for the TV-$L_1$ optical flow problem

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo

In this study, we address the problem of computing efficiently a dense optical flow between two images under a total variation (TV) regularization and an

L_1

norm data fidelity constraint using a variational method. We build upon Nesterov's framework for ...

2010