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» Learning Low-Level Vision
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ICPR
2006
IEEE
14 years 10 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...
ICPR
2006
IEEE
14 years 10 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...
ICPR
2006
IEEE
14 years 10 months ago
Supervised Image Classification by SOM Activity Map Comparison
This article presents a method aiming at quantifying the visual similarity between two images. This kind of problem is recurrent in many applications such as object recognition, i...
Grégoire Lefebvre, Christophe Laurent, Juli...
ICPR
2006
IEEE
14 years 10 months ago
High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction
We aim to improve the accuracy of handwritten Chinese character recognition using two advanced techniques: discriminative feature extraction (DFE) and discriminative learning quad...
Cheng-Lin Liu
ICPR
2006
IEEE
14 years 10 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen