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» Budgeted Nonparametric Learning from Data Streams
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MIA
2011
111views more  MIA 2011»
14 years 8 months ago
Segmenting the prostate and rectum in CT imagery using anatomical constraints
The automatic segmentation of the prostate and rectum from 3-D computed tomography (CT) images is still a challenging problem, and is critical for image-guided therapy application...
Siqi Chen, D. Michael Lovelock, Richard J. Radke
AROBOTS
2011
14 years 9 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
JMLR
2010
130views more  JMLR 2010»
14 years 8 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
CVPR
2009
IEEE
15 years 5 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
114
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APWEB
2005
Springer
15 years 7 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang