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AROBOTS
2004
99views more  AROBOTS 2004»
15 years 3 months ago
Bayesian Robot Programming
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...
Olivier Lebeltel, Pierre Bessière, Julien D...
149
Voted
JVCIR
2010
147views more  JVCIR 2010»
15 years 2 months ago
Modeling, classifying and annotating weakly annotated images using Bayesian network
We propose a probabilistic graphical model to represent weakly annotated images1 . This model is used to classify images and automatically extend existing annotations to new image...
Sabine Barrat, Salvatore Tabbone
147
Voted
ICPR
2010
IEEE
15 years 1 months ago
Adaptive Motion Model for Human Tracking Using Particle Filter
This paper presents a novel approach to model the complex motion of human using a probabilistic autoregressive moving average model. The parameters of the model are adaptively tun...
Mohammad Hossein Ghaeminia, Amir Hossein Shabani, ...
164
Voted
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
15 years 1 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
149
Voted
ACL
2011
14 years 7 months ago
An Unsupervised Model for Joint Phrase Alignment and Extraction
We present an unsupervised model for joint phrase alignment and extraction using nonparametric Bayesian methods and inversion transduction grammars (ITGs). The key contribution is...
Graham Neubig, Taro Watanabe, Eiichiro Sumita, Shi...