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» Objective Functions for Feature Discrimination
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180
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VLSISP
2010
254views more  VLSISP 2010»
15 years 1 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
125
Voted
CVPR
2001
IEEE
16 years 4 months ago
Learning Spatially Localized, Parts-Based Representation
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
110
Voted
CVPR
2007
IEEE
16 years 4 months ago
Modulation Domain Template Tracking
For the first time, we perform normalized correlation template tracking in the modulation domain. For each frame of the video sequence, we compute a multi-component AM-FM image mo...
Chuong T. Nguyen, Joseph P. Havlicek, Mark B. Year...
ICPR
2006
IEEE
16 years 3 months ago
Target Model Estimation using Particle Filters for Visual Servoing
In this paper, we present a novel method for model estimation for visual servoing. This method employs a particle filter algorithm to estimate the depth of the image features onli...
A. H. Abdul Hafez, C. V. Jawahar
124
Voted
ICML
2007
IEEE
16 years 3 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum