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» A comparative study of two object recognition methods
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ESANN
2006
15 years 8 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
16 years 1 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 10 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
16 years 9 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»
15 years 5 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