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» A comparative study of two object recognition methods
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ESANN
2006
14 years 11 months ago
Recognition of handwritten digits using sparse codes generated by local feature extraction methods
We investigate when sparse coding of sensory inputs can improve performance in a classification task. For this purpose, we use a standard data set, the MNIST database of handwritte...
Rebecca Steinert, Martin Rehn, Anders Lansner
SIGIR
2006
ACM
15 years 3 months ago
Identifying comparative sentences in text documents
This paper studies the problem of identifying comparative sentences in text documents. The problem is related to but quite different from sentiment/opinion sentence identification...
Nitin Jindal, Bing Liu
MCS
2000
Springer
15 years 1 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
CVPR
2005
IEEE
15 years 11 months ago
Shape Matching and Object Recognition Using Low Distortion Correspondences
We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up corres...
Alexander C. Berg, Tamara L. Berg, Jitendra Malik
PAMI
2010
185views more  PAMI 2010»
14 years 8 months ago
Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...
Petr Somol, Jana Novovicová