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» A Model Selection Approach for Local Learning
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ICPR
2006
IEEE
15 years 11 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini
ICCV
2003
IEEE
15 years 11 months ago
Controlling Model Complexity in Flow Estimation
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
ECCV
2008
Springer
15 years 11 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele

Publication
433views
15 years 6 months ago
Optimal Feature Selection for Subspace Image Matching
Image matching has been a central research topic in computer vision over the last decades. Typical approaches for correspondence involve matching features between images. In this p...
Gemma Roig, Xavier Boix, Fernando De la Torre
ISIPTA
2003
IEEE
125views Mathematics» more  ISIPTA 2003»
15 years 3 months ago
Game-Theoretic Learning Using the Imprecise Dirichlet Model
We discuss two approaches for choosing a strategy in a two-player game. We suppose that the game is played a large number of rounds, which allows the players to use observations o...
Erik Quaeghebeur, Gert de Cooman