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Domain Adaptation for Microscopy Imaging

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Sparse Binary Features for Image Classification

Johann Paratte

In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...

2013

Mirror Match: Reliable Feature Point Matching Without Geometric Constraints

Sabine Süsstrunk, Stefan Winkler

Many algorithms have been proposed to solve the problem of matching feature points in two or more images using geometric assumptions to increase the robustness of the matching. However, these assumptions do not always hold; in particular, few methods addre ...

2013

Advanced Image Processing for Biology, and the Open Bio Image Alliance (OBIA)

Michaël Unser, Daniel Sage, Ricard Delgado Gonzalo

The field of biological imaging has evolved considerably during the past decade as a result of recent (r)evolutions in fluorescence labeling and optical microscopy. Bioimage informatics has been identified as a top priority to cope with the ever-increasing ...

EUSIPCO2013

Transformation-Invariant Analysis of Visual Signals with Parametric Models

Elif Vural

The analysis of collections of visual data, e.g., their classification, modeling and clustering, has become a problem of high importance in a variety of applications. Meanwhile, image data captured in uncontrolled environments by arbitrary users is very li ...

EPFL2013

Graph Matching for Adaptation in Remote Sensing

Devis Tuia

We present an adaptation algorithm focused on the description of the data changes under different acquisition conditions. When considering a source and a destination domain, the adaptation is carried out by transforming one data set to the other using an a ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Learning Image Descriptors with the Boosting-Trick

Pascal Fua, Vincent Lepetit, Tomasz Piotr Trzcinski, Christos Marios Christoudias

In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...

2012

Fast Parametric Snakes For 3D Microscopy

Michaël Unser, Ricard Delgado Gonzalo

We present a new fast active contour for images in 3D microscopy. We introduce a fully parametric design that relies on exponential B-spline bases and allows us to impose a sphere-like topology. The proposed 3D snake can approximate blob-like objects with ...

Ieee2012

Fast Parametric Snakes for 3D Microscopy

Michaël Unser, Ricard Delgado Gonzalo

IEEE2012

Comparison of Deconvolution Software: A User Point of View—Part 2

Daniel Sage, Alessandra Griffa

Deconvolution is an image processing technique that restores the effective object representation [3] [4], allowing to improve images analysis steps such as segmentation [1] or colocalization study [2]. We performed several deconvolution tests on different ...

EMS2010

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009