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ICPR
2010
IEEE
13 years 11 months ago
Motif Discovery and Feature Selection for CRF-Based Activity Recognition
Abstract—Due to their ability to model sequential data without making unnecessary independence assumptions, conditional random fields (CRFs) have become an increasingly popular ...
Liyue Zhao, Xi Wang, Gita Sukthankar
ICCPOL
2009
Springer
13 years 3 months ago
A Simple and Efficient Model Pruning Method for Conditional Random Fields
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Hai Zhao, Chunyu Kit
IJCAI
2007
13 years 7 months ago
Training Conditional Random Fields Using Virtual Evidence Boosting
While conditional random fields (CRFs) have been applied successfully in a variety of domains, their training remains a challenging task. In this paper, we introduce a novel trai...
Lin Liao, Tanzeem Choudhury, Dieter Fox, Henry A. ...
IHI
2010
219views Healthcare» more  IHI 2010»
13 years 19 days ago
Conditional random fields for activity recognition in smart environments
One of the most common functions of smart environments is to monitor and assist older adults with their activities of daily living. Activity recognition is a key component in this...
Ehsan Nazerfard, Barnan Das, Lawrence B. Holder, D...
ICCV
2003
IEEE
14 years 7 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan