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» Feature Extraction Using ICA
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EMNLP
2009
13 years 7 months ago
On the Role of Lexical Features in Sequence Labeling
We use the technique of SVM anchoring to demonstrate that lexical features extracted from a training corpus are not necessary to obtain state of the art results on tasks such as N...
Yoav Goldberg, Michael Elhadad
WACV
2005
IEEE
14 years 2 months ago
Shared Features for Scalable Appearance-Based Object Recognition
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
Erik Murphy-Chutorian, Jochen Triesch
CVRMED
1995
Springer
14 years 26 days ago
Comparison of Feature-Based Matching of CT and MR Brain Images
Geometrical image features like edges and ridges in digital images may be extracted by convolving the images with appropriate derivatives of Gaussians. The choice of the convolutio...
J. B. Antoine Maintz, Petra A. van den Elsen, Max ...
ECIR
2007
Springer
13 years 10 months ago
Evaluating Query-Independent Object Features for Relevancy Prediction
Abstract. This paper presents a series of experiments investigating the effectiveness of query-independent features extracted from retrieved objects to predict relevancy. Features...
Andrés R. Masegosa, Hideo Joho, Joemon M. J...
ICCV
2011
IEEE
12 years 9 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry