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» Forecasting high-dimensional data
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CVPR
2009
IEEE
16 years 5 months ago
SIFT-Rank: Ordinal Description for Invariant Feature Correspondence
This paper investigates ordinal image description for invariant feature correspondence. Ordinal description is a meta-technique which considers image measurements in terms of th...
Matthew Toews, William M. Wells III
CVPR
2004
IEEE
15 years 12 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang
IPMI
2003
Springer
15 years 10 months ago
Permutation Tests for Classification: Towards Statistical Significance in Image-Based Studies
Abstract. Estimating statistical significance of detected differences between two groups of medical scans is a challenging problem due to the high dimensionality of the data and th...
Polina Golland, Bruce Fischl
ICIP
2007
IEEE
15 years 4 months ago
Adaptive Cluster-Distance Bounding for Nearest Neighbor Search in Image Databases
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Sharadh Ramaswamy, Kenneth Rose
SAC
2006
ACM
15 years 3 months ago
Schemes for SR-Tree packing
Modern database applications like geographic information systems, multimedia databases, and digital libraries dealing with huge volumes of high dimensional data, make use of multi...
Jayendra Venkateswaran, S. R. Subramanya