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CLOR
2006
14 years 16 days ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Ilkay Ulusoy, Christopher M. Bishop
AI
2004
Springer
13 years 8 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
CVPR
1996
IEEE
14 years 10 months ago
Combining greyvalue invariants with local constraints for object recognition
This paper addresses the problem of recognizing objects in large image databases. The method is based on local characteristics which are invariant to simzlarity transformations in...
Cordelia Schmid, Roger Mohr
CVPR
2008
IEEE
14 years 10 months ago
Object recognition and segmentation by non-rigid quasi-dense matching
In this paper, we present a non-rigid quasi-dense matching method and its application to object recognition and segmentation. The matching method is based on the match propagation...
Esa Rahtu, Janne Heikkilä, Juho Kannala, Sami...
CVPR
1996
IEEE
14 years 29 days ago
Global Minimum for Active Contour Models: A Minimal Path Approach
A new boundary detection approach for shape modeling is presented. It detects the global minimum of an active contour model's energy between two end points. Initialization is ...
Laurent D. Cohen, Ron Kimmel