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» Stochastic Motif Extraction Using Hidden Markov Model
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ACL
2006
14 years 11 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
ICIP
2002
IEEE
15 years 11 months ago
Extract highlights from baseball game video with hidden Markov models
In this paper, we describe a statistical method to detect highlights in a baseball game video. The input video is first segmented into scene shots, within which the camera motion ...
Peng Chang, Mei Han, Yihong Gong
BMCBI
2007
141views more  BMCBI 2007»
14 years 9 months ago
Using structural motif descriptors for sequence-based binding site prediction
Background: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, ...
Andreas Henschel, Christof Winter, Wan Kyu Kim, Mi...
BMCBI
2011
14 years 1 months ago
Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs
Background: One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Results:...
Leslie Regad, Juliette Martin, Anne-Claude Camprou...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
14 years 4 months ago
Aggregation-based model reduction of a Hidden Markov Model
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Kun Deng, Prashant G. Mehta, Sean P. Meyn