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113
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DAGM
2006
Springer
15 years 4 months ago
On-Line, Incremental Learning of a Robust Active Shape Model
Abstract. Active Shape Models are commonly used to recognize and locate different aspects of known rigid objects. However, they require an off-line learning stage, such that the ex...
Michael Fussenegger, Peter M. Roth, Horst Bischof,...
99
Voted
NIPS
2004
15 years 1 months ago
Learning first-order Markov models for control
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...
Pieter Abbeel, Andrew Y. Ng
ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 14 days ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
115
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IJRR
2006
119views more  IJRR 2006»
15 years 15 days ago
Predicting the Performance of Cooperative Simultaneous Localization and Mapping (C-SLAM)
In this paper we study the time evolution of the position estimates' covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper boun...
Anastasios I. Mourikis, Stergios I. Roumeliotis
112
Voted
WINET
2010
88views more  WINET 2010»
14 years 11 months ago
Tree-based object tracking without mobility statistics in wireless sensor networks
Object tracking in wireless sensor networks is to track mobile objects by scattered sensors. These sensors are typically organized into a tree to deliver report messages upon dete...
Li-Hsing Yen, Bang Ye Wu, Chia-Cheng Yang