1864 search results - page 26 / 373 » Modeling Classification and Inference Learning |
ECCV
2010
Springer
14 years 2 months ago
2010
Springer
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
BMCBI
2010
13 years 9 months ago
2010
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
14 years 2 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
EMNLP
2006
13 years 10 months ago
2006
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
CVPR
2009
IEEE
15 years 4 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...