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» Learning Mid-Level Features For Recognition
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SGAI
2004
Springer
14 years 28 days ago
Interactive Selection of Visual Features through Reinforcement Learning
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Sébastien Jodogne, Justus H. Piater
DAGM
2009
Springer
14 years 2 months ago
Learning with Few Examples by Transferring Feature Relevance
The human ability to learn difficult object categories from just a few views is often explained by an extensive use of knowledge from related classes. In this work we study the use...
Erik Rodner, Joachim Denzler
EMNLP
2008
13 years 9 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu
CVPR
2007
IEEE
14 years 9 months ago
Eigenboosting: Combining Discriminative and Generative Information
A major shortcoming of discriminative recognition and detection methods is their noise sensitivity, both during training and recognition. This may lead to very sensitive and britt...
Helmut Grabner, Peter M. Roth, Horst Bischof
ICIP
2008
IEEE
14 years 9 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....