65 search results - page 12 / 13 » Is Nonparametric Learning Practical in Very High Dimensional... |
ICIP
2006
IEEE
14 years 7 months ago
2006
IEEE
Linear techniques are widely used to reduce the dimension of image representation spaces in applications such as image indexing and object recognition. Optimal Component Analysis ...
IIS
2003
13 years 7 months ago
2003
Text clustering typically involves clustering in a high dimensional space, which appears difficult with regard to virtually all practical settings. In addition, given a particular...
ICPP
2000
IEEE
13 years 10 months ago
2000
IEEE
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
FIMH
2009
Springer
13 years 3 months ago
2009
Springer
Cardiac magnetic resonance (MR) imaging has advanced to become a powerful diagnostic tool in clinical practice. Automatic detection of anatomic landmarks from MR images is importan...
PAA
2002
13 years 5 months ago
2002
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...