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» Adaptive Kernel Methods Using the Balancing Principle
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ECCV
2002
Springer
14 years 9 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
TREC
2008
13 years 9 months ago
A Study of Adaptive Relevance Feedback - UIUC TREC 2008 Relevance Feedback Experiments
In this paper, we report our experiments in the TREC 2008 Relevance Feedback Track. Our main goal is to study a novel problem in feedback, i.e., optimization of the balance of the...
Yuanhua Lv, ChengXiang Zhai
ICCV
2005
IEEE
14 years 9 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
CVPR
2001
IEEE
14 years 9 months ago
Small Sample Learning during Multimedia Retrieval using BiasMap
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...
Xiang Sean Zhou, Thomas S. Huang
LCPC
2009
Springer
14 years 3 days ago
Using the Meeting Graph Framework to Minimise Kernel Loop Unrolling for Scheduled Loops
This paper improves our previous research effort [1] by providing an efficient method for kernel loop unrolling minimisation in the case of already scheduled loops, where circular...
Mounira Bachir, David Gregg, Sid Ahmed Ali Touati