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» Learning Mid-Level Features For Recognition
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ICPR
2004
IEEE
14 years 8 months ago
Learning High-level Independent Components of Images through a Spectral Representation
Statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. Here we extend these methods for le...
Aapo Hyvärinen, Jussi T. Lindgren
PPSN
1990
Springer
13 years 11 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu
LREC
2010
157views Education» more  LREC 2010»
13 years 9 months ago
Is Sentiment a Property of Synsets? Evaluating Resources for Sentiment Classification using Machine Learning
Existing approaches to classifying documents by sentiment include machine learning with features created from n-grams and part of speech. This paper explores a different approach ...
Aleksander Wawer
CVPR
2006
IEEE
14 years 9 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ICML
2010
IEEE
13 years 8 months ago
Rectified Linear Units Improve Restricted Boltzmann Machines
Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all ...
Vinod Nair, Geoffrey E. Hinton