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» Learning Flexible Features for Conditional Random Fields
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COLING
2008
15 years 1 months ago
An Integrated Probabilistic and Logic Approach to Encyclopedia Relation Extraction with Multiple Features
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Xiaofeng Yu, Wai Lam
AAAI
2008
15 years 2 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso
DAS
2010
Springer
15 years 1 months ago
Overlapped text segmentation using Markov random field and aggregation
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Xujun Peng, Srirangaraj Setlur, Venu Govindaraju, ...
SIGIR
2009
ACM
15 years 6 months ago
An improved markov random field model for supporting verbose queries
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
Matthew Lease
ICPR
2004
IEEE
16 years 27 days ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic