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Publications associées (207)

Spin Glass Models of Markov Random Fields

This paper presents a novel algorithm for robust object recognition. We propose to model the visual appearance of objects via probability density functions. The algorithm consists of a fully connected Markov random field with energy function derived from r ...

2006

Learning to Retrieve Images from Text Queries with a Discriminative Model

Samy Bengio, David Grangier, Florent Monay Michaud

This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval performance of the model. For that purpose, we rely on a ranking loss which ha ...

2006

Learning to Retrieve Images from Text Queries with a Discriminative Model

Samy Bengio, David Grangier, Florent Monay Michaud

IDIAP2006

A Discriminative Approach to Robust Visual Place Recognition

Barbara Caputo

An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization is performed based on a purely geo ...

2006

Integrating co-occurrence and spatial contexts on patch-based scene segmentation

Daniel Gatica-Perez, Jean-Marc Odobez, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific le ...

2006

Probabilistic Message Passing in Peer Data Management Systems

Karl Aberer, Philippe Cudré-Mauroux

Until recently, most data integration techniques involved central components, e.g., global schemas, to enable transparent access to heterogeneous databases. Today, however, with the democratization of tools facilitating knowledge elicitation in machine-pro ...

IEEE2006

Posterior Based Keyword Spotting with A Priori Thresholds

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

In this paper, we propose a new posterior based scoring approach for keyword and non keyword (garbage) elements. The estimation of these scores is based on HMM state posterior probability definition, taking into account long contextual information and the ...

2006

Posterior Based Keyword Spotting with A Priori Thresholds

Hervé Bourlard, Samy Bengio, Hamed Ketabdar

IDIAP2006

Second-order hyperbolic S.P.D.E.'s driven by homogeneous Gaussian noise on a hyperplane

Robert Dalang, Olivier Lévêque

We study a class of hyperbolic stochastic partial di®erential equations in Euclidean space, that includes the wave equation and the telegraph equation, driven by Gaussian noise concentrated on a hyperplane. The noise is assumed to be white in time but spat ...

2006

Kernel Methods for Melanoma Recognition

Barbara Caputo, Tatiana Tommasi

Skin cancer is a spreading disease in the western world. Early detection and treatment are crucial for improving the patient survival rate. In this paper we present two algorithms for computer assisted diagnosis of melanomas. The first is the support vecto ...

2006

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