Personne

Sofia Karygianni

Cette personne n’est plus à l’EPFL

Bulged Eardrum Detection From 3D Data

Pascal Frossard, Ivana Tosic, Sofia Karygianni

Bulging is a medical characteristic of the eardrum that is crucial for the diagnosis of acute otitis media. This work proposes a novel classification method for distinguishing bulged eardrums from non-bulged ones. The method uses novel key features extract ...

IEEE2018

Automated Eardrum Registration From Light-Field Data

Pascal Frossard, Ivana Tosic, Sofia Karygianni

The performance of automated classification algorithms for medical images needs to be very high and especially robust in order to be adopted into healthcare. Most of the time the main challenge is unregistered data, since it is usually captured: 1) from di ...

IEEE2018

Sparse molecular image representation

Pascal Frossard, Sofia Karygianni

Sparsity-based models have proven to be very effective in most image processing applications. The notion of sparsity has recently been extended to structured sparsity models where not only the number of components but also their support is important. This ...

Elsevier2016

Learning from sparse codes

Pascal Frossard, Sofia Karygianni

In this paper we address the problem of learning image structures directly from sparse codes. We first model images as linear combinations of molecules, which are themselves groups of atoms from a redundant dictionary. We then formulate a new structure lea ...

Ieee2016

Signal structure: from manifolds to molecules and structured sparsity

Sofia Karygianni

Effective representation methods and proper signal priors are crucial in most signal processing applications. In this thesis we focus on different structured models and we design appropriate schemes that allow the discovery of low dimensional latent struct ...

EPFL2015

Structured Sparse Coding for Image Denoising or Pattern Detection

Pascal Frossard, Sofia Karygianni

Sparsity has been one of the major drives in signal processing in the last decade. Structured sparsity has also lately emerged as a way to enrich signal priors towards more meaningful and accurate representations. In this paper we propose a new structured ...

2014

Linear Manifold Approximation based on Differences of Tangents

Pascal Frossard, Sofia Karygianni

In this paper, we consider the problem of manifold approximation with affine subspaces. Our objective is to discover a set of low dimensional affine subspaces that represents manifold data accurately while preserving the manifold’s structure. For this purp ...

2011