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NC
2002
196views Neural Networks» more  NC 2002»
13 years 8 months ago
Beyond second-order statistics for learning: A pairwise interaction model for entropy estimation
Second order statistics have formed the basis of learning and adaptation due to its appeal and analytical simplicity. On the other hand, in many realistic engineering problems requ...
Deniz Erdogmus, José Carlos Príncipe...
CVPR
2012
IEEE
11 years 11 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
GEOINFORMATICA
1998
96views more  GEOINFORMATICA 1998»
13 years 8 months ago
Experiments with Learning Techniques for Spatial Model Enrichment and Line Generalization
The nature of map generalization may be non-uniform along the length of an individual line, requiring the application of methods that adapt to the local geometry and the geographi...
Corinne Plazanet, Nara Martini Bigolin, Anne Ruas
ICAPR
2009
Springer
13 years 6 months ago
Online Improved Eigen Tracking
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
Subarna Tripathi, Santanu Chaudhury, Sumantra Dutt...
AROBOTS
2011
13 years 3 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