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PAMI
2008
176views more  PAMI 2008»
13 years 7 months ago
Learning Flexible Features for Conditional Random Fields
Abstract-- Extending traditional models for discriminative labeling of structured data to include higher-order structure in the labels results in an undesirable exponential increas...
Liam Stewart, Xuming He, Richard S. Zemel
CVIU
2006
222views more  CVIU 2006»
13 years 7 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
EMNLP
2008
13 years 9 months ago
Revealing the Structure of Medical Dictations with Conditional Random Fields
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
Jeremy Jancsary, Johannes Matiasek, Harald Trost
ISVC
2007
Springer
14 years 1 months ago
Learning to Recognize Complex Actions Using Conditional Random Fields
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...
Christopher I. Connolly
NIPS
2008
13 years 9 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...