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» Hierarchical Hidden Markov Models for Information Extraction
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NLDB
2005
Springer
15 years 7 months ago
Combining Data-Driven Systems for Improving Named Entity Recognition
Abstract. The increasing flow of digital information requires the extraction, filtering and classification of pertinent information from large volumes of texts. An important pre...
Zornitsa Kozareva, Óscar Ferrández, ...
ICIP
2008
IEEE
16 years 3 months ago
Robust snake convergence based on dynamic programming
The extraction of contours using deformable models, such as snakes, is a problem of great interest in computer vision, particular in areas of medical imaging and tracking. Snakes ...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 6 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
AIPS
2008
15 years 3 months ago
HiPPo: Hierarchical POMDPs for Planning Information Processing and Sensing Actions on a Robot
Flexible general purpose robots need to tailor their visual processing to their task, on the fly. We propose a new approach to this within a planning framework, where the goal is ...
Mohan Sridharan, Jeremy L. Wyatt, Richard Dearden
PRICAI
2004
Springer
15 years 6 months ago
Classifying Human Actions Using an Incomplete Real-Time Pose Skeleton
Currently, most human action recognition systems are trained with feature sets that have no missing data. Unfortunately, the use of human pose estimation models to provide more des...
Patrick Peursum, Hung Hai Bui, Svetha Venkatesh, G...