Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

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Noise Analysis For Environmental Loading Effect On Gps Position Time Series

Feng Zhou, Jean-Philippe Lucien Montillet

This paper focusses on the impact of environment mass loading on GPS time-series of position changes and noise characteristic. We make use of position time series of 206 GPS station ranging from 2001 to 2013 globally distributed. Firstly, we investigate th ...

Institute of Rock Structure and Mechanics, AS CR2017

A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

Jean-Philippe Thiran, Martin Proença, Fabian Braun

Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Volkan Cevher

The estimation of a random vector with independent components passed through a linear transform followed by a componentwise (possibly nonlinear) output map arises in a range of applications. Approximate message passing (AMP) methods, based on Gaussian appr ...

2016

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

Object segmentation and ground truth in 3D embryonic imaging

Andrew Charles Oates

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Her ...

2016

Design of a Distributed Quantized Luenberger Filter for Bounded Noise

Colin Neil Jones, Andrea Alessandretti, Ye Pu, Francisco Fernandes Castro Rego

This paper addresses the problem of distributed state estimation for linear systems with process and measurement noise, in the case of limited communication data rate, where the data exchanged between agents is quantized. We propose a linear distributed Lu ...

Ieee2016

Learning Structured Models for Segmentation of 2D and 3D Imagery

Pascal Fua, Graham Knott, Kevin Smith, Aurélien Lucchi, Yunpeng Li, Carlos Joaquin Becker, Pablo Marquez Neila

Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal perfo ...

Institute of Electrical and Electronics Engineers2015

Expectation Propagation for Rectified Linear Poisson Regression

Young Jun Ko, Matthias Seeger

The Poisson likelihood with rectified linear function as non-linearity is a physically plausible model to discribe the stochastic arrival process of photons or other particles at a detector. At low emission rates the discrete nature of this process leads t ...

2015

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