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» On the Use of Virtual Evidence in Conditional Random Fields
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CVPR
2006
IEEE
14 years 9 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...
CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Segmentation of Objects using Efficient Learning
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
NIPS
2003
13 years 9 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
AAAI
2011
12 years 7 months ago
Mean Field Inference in Dependency Networks: An Empirical Study
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
Daniel Lowd, Arash Shamaei
INTERSPEECH
2010
13 years 2 months ago
Efficient combined approach for named entity recognition in spoken language
We focus in this paper on the named entity recognition task in spoken data. The proposed approach investigates the use of various contexts of the words to improve recognition. Exp...
Azeddine Zidouni, Sophie Rosset, Hervé Glot...