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» Minimal Kernel Classifiers
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ICCV
2005
IEEE
15 years 3 months ago
Fast Global Kernel Density Mode Seeking with Application to Localisation and Tracking
We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
CVPR
2012
IEEE
13 years 9 days ago
Supervised hashing with kernels
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised ...
Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, Shi...
BMCBI
2006
110views more  BMCBI 2006»
14 years 10 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
CVPR
2008
IEEE
15 years 12 months ago
Image partial blur detection and classification
In this paper, we propose a partially-blurred-image classification and analysis framework for automatically detecting images containing blurred regions and recognizing the blur ty...
Renting Liu, Zhaorong Li, Jiaya Jia
JNS
2008
44views more  JNS 2008»
14 years 9 months ago
The Scaling Attractor and Ultimate Dynamics for Smoluchowski's Coagulation Equations
We describe a basic framework for studying dynamic scaling that has roots in dynamical systems and probability theory. Within this framework, we study Smoluchowski's coagulat...
Govind Menon, Robert L. Pego