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» The Infinite Hidden Markov Model
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88
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ICPR
2006
IEEE
16 years 6 days ago
A Combined Bayesian Markovian Approach for Behaviour Recognition
Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although the...
David Paul Young, James M. Ferryman, Nicholas L. C...
79
Voted
BMCBI
2008
103views more  BMCBI 2008»
14 years 11 months ago
Parameter estimation for robust HMM analysis of ChIP-chip data
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Peter Humburg, David Bulger, Glenn Stone
INTERSPEECH
2010
14 years 6 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng
ICCV
2003
IEEE
15 years 4 months ago
Markov-Based Failure Prediction for Human Motion Analysis
This paper presents a new method of detecting and predicting motion tracking failures with applications in human motion and gait analysis. We define a tracking failure as an event...
Shiloh L. Dockstader, Nikita S. Imennov, A. Murat ...
ICMCS
2006
IEEE
344views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Pattern Mining in Visual Concept Streams
Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of ...
Lexing Xie, Shih-Fu Chang