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» Factorial Hidden Markov Models for Gait Recognition
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ICPR
2006
IEEE
14 years 8 months ago
Detecting Coarticulation in Sign Language using Conditional Random Fields
Coarticulation is one of the important factors that makes automatic sign language recognition a hard problem. Unlike in speech recognition, coarticulation effects in sign language...
Ruiduo Yang, Sudeep Sarkar
ICDAR
2003
IEEE
14 years 27 days ago
On Machine Understanding of Online Handwritten Mathematical Expressions
This paper aims at automatic recognition of online handwritten mathematical expressions written on an electronic tablet. The proposed technique involves two major stages: symbol r...
Utpal Garain, B. B. Chaudhuri
LREC
2010
188views Education» more  LREC 2010»
13 years 9 months ago
Example-Based Automatic Phonetic Transcription
Current state-of-the-art systems for automatic phonetic transcription (APT) are mostly phone recognizers based on Hidden Markov models (HMMs). We present a different approach for ...
Christina Leitner, Martin Schickbichler, Stefan Pe...
ERCIMDL
2007
Springer
159views Education» more  ERCIMDL 2007»
14 years 1 months ago
Reducing Costs for Digitising Early Music with Dynamic Adaptation
Abstract. Optical music recognition (OMR) enables librarians to digitise early music sources on a large scale. The cost of expert human labour to correct automatic recognition erro...
Laurent Pugin, John Ashley Burgoyne, Ichiro Fujina...
RECOMB
2005
Springer
14 years 8 months ago
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...