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» Spatial Representation for Efficient Sequence Classification
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ICPR
2010
IEEE
13 years 8 months ago
Spatial Representation for Efficient Sequence Classification
We present a general, simple feature representation of sequences that allows efficient inexact matching, comparison and classification of sequential data. This approach, recently ...
Pavel Kuksa, Vladimir Pavlovic
ISMB
1993
13 years 6 months ago
Computationally Efficient Cluster Representation in Molecular Sequence Megaclassification
Molecular sequence megaclassification is a technique for automated protein sequence analysis and annotation. Implementation of the method has been limited by the need to store and...
David J. States, Nomi L. Harris, Lawrence Hunter
CHI
2006
ACM
14 years 5 months ago
3D and sequential representations of spatial relationships among photos
This paper proposes automatic representations of spatial relationships among photos for structure analysis and review of a photographic subject. Based on camera tracking, photos a...
Mahoro Anabuki, Hiroshi Ishii
ECCV
2010
Springer
13 years 9 months ago
Kernel Sparse Representation for Image Classification and Face Recognition
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
CVPR
2010
IEEE
14 years 29 days ago
Sufficient Dimensionality Reduction for Visual Sequence Classification
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...
Alex Shyr, Raquel Urtasun, Michael Jordan