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Steer&Detect on Images 14 Nov 2017

Julien Fageot
EPFL STI LIB

Fundamental computational barriers in inverse problems and the mathematics of information27 Oct 2017

Alexander Bastounis
Cambridge University

Variational use of B-splines and Kernel Based Functions27 Oct 2017

Christophe Rabut
INSA Toulouse

Kernel Based Functions are generalizations of spline functions and radial basis functions. These R^d to R functions are in the form f = \sum_{i=1}^n λi φ(x−xi) or \sum_{i=1}^n λi φ(x−xi)+pk(x) where φ is called the kernel, (xi)_{i=1:n} ∈ (R^d)^n are the so called centers of f, (λi)_{i=1:n} are real coefficients, and pk is some degree k polynomial. When φ is a bell shaped function meeting some property (such as, in particular \sum_{i=1}^n φ(x) = 1 for any x ∈ R^d), we write it B and call it, for short, B-spline. In this talk we present two particular uses of these Kernel Based Functions, and a property of a specific polynomial interpolation. First, hierarchical B-splines: using B-splines of different scales, and a mean square optimization, we show how to approximate scattered data with possibility of zoom on some regions, adaptively from the data. We so obtain locally tensor product functions, where the grid of the centers is finer in some regions and coarser in other regions. Second, in a CAGD aim and using modified (variational) Bézier curves or surfaces, we show that it is possible to derive B-spline curves or surfaces being closer to (or further from) the control polygon, while being in the same vectorial space. This gives more flexibility to easily derive new forms. Third we present variational polynomial interpolation, which is true polynomial interpolation of any given data, and so obtain a polynomial interpolation without the famous Runge oscillations. These interpolating polynomials converge towards the interpolating polynomial spline of the data.

Deep learning based data manifold projection - a new regularization for inverse problems17 Oct 2017

Harshit Gupta
EPFL STI LIB

GlobalBioIm Lib - v2: new tools, more flexibility, and improved composition rules.03 Oct 2017

Emmanuel Soubies
EPFL STI LIB

Exact Discretization of Continuous-Domain Linear Inverse Problems with Generalized TV Regularization Using B-Splines​24 Aug 2017

Thomas Debarre
EPFL STI LIB

Fractional Integral transforms and Time-Frequency Representations02 Jun 2017

Prof. Ahmed I. Zayed
Department of Mathematical Sciences DePaul University

First steps toward fast PET reconstruction30 May 2017

Mike McCann
EPFL STI LIB

Lipid membranes and surface reconstruction - a biologically inspired method for 3D segmentation16 May 2017

Nicolas Chiaruttini
University of Geneva

Optical Diffraction Tomography: Principles and Algorithms09 May 2017

Thanh-an Pham
EPFL STI LIB

Compressed Sensing for Dose Reduction in STEM Tomography11 Apr 2017

Laurène Donati
EPFL STI LIB

Chasing Mycobacteria10 Apr 2017

Virginie Uhlmann
EPFL STI LIB

Multifractal analysis for signal and image classification23 Mar 2017

Stéphane Jaffard
UPEC

3D SIM and measurements time-reallocation for scanning based systems: Introduction and preliminary results on these two problems14 Mar 2017

Emmanuel Soubies
EPFL STI LIB

Inverse problems and multimodality for biological imaging28 Feb 2017

Denis Fortun
EPFL STI LIB

RKHS to find the Representer Theorem for regularization operators whose null space is not finite dimensional09 Feb 2017

Harshit Gupta
EPFL STI LIB

A unified reconstruction framework for coherent imaging24 Jan 2017

Ferréol Soulez
EPFL STI LIB

BPConvNet for compressed sensing recovery in bioimaging10 Jan 2017

Kyong Jin
EPFL STI LIB

Steerable template detection based on maximum correlation: preliminary results13 Dec 2016

Adrien Depeursinge
EPFL STI LIB

Opportunities in Computational Imaging for Biomicroscopy06 Dec 2016

Prof. Michael Leibling
Idap Research Institute

A multiple scattering approach to diffraction tomography30 Nov 2016

Luc Zeng
EPFL STI LIB

Learning Optimal Shrinkage Splines for ADMM Algorithms22 Nov 2016

Ha Nguyen
EPFL STI LIB

SIGGRAPH ASIA 201601 Nov 2016

Daniel Schmitter
EPFL STI LIB

Lévy's Persian summers18 Oct 2016

Julien Fageot
EPFL STI LIB

High-quality parallel-ray X-ray CT back projection using optimized interpolation11 Oct 2016

Mike McCann
EPFL STI LIB

Algorithmic Aspects of Compressive Sensing03 Oct 2016

Verner Vlacic
Cambridge University

ICIP 201620 Sep 2016

Anaïs Badoual
EPFL STI LIB

Machine Vision forum in Heidelberg17 Aug 2016

Virginie Uhlmann
EPFL STI LIB

K-space interpolation using CV(complex valued)-CNN & sparse and low-rank model of ALOHA09 Aug 2016

Kyong Jin
EPFL STI LIB

Complete Compressed Sensing Framework for STEM Tomography19 Jul 2016

Laurène Donati
EPFL STI LIB

Trainable shrinkage splines: inverse problems meet deep learning28 Jun 2016

Ha Nguyen
EPFL STI LIB

A reconstruction framework for coherent imaging31 May 2016

Ferréol Soulez
EPFL STI LIB

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