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NIPS
2008
14 years 11 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ICIAP
2001
Springer
15 years 10 months ago
2D Shape Recognition by Hidden Markov Models
In Computer Vision, two-dimensional shape classifcation is a complex and well studied topic, often basic for three-dimensional object recognition. Object contours are a widely cho...
Manuele Bicego, Vittorio Murino
BMCBI
2004
208views more  BMCBI 2004»
14 years 9 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
ICIP
2008
IEEE
15 years 11 months ago
Conditional iterative decoding of Two Dimensional Hidden Markov Models
Two Dimensional Hidden Markov Models (2D-HMMs) provide substantial benefits for many computer vision and image analysis applications. Many fundamental image analysis problems, inc...
Mehmet Emre Sargin, Alphan Altinok, Kenneth Rose, ...
PAA
2006
14 years 9 months ago
Audio-visual sports highlights extraction using Coupled Hidden Markov Models
We present our studies on the application of Coupled Hidden Markov Models(CHMMs) to sports highlights extraction from broadcast video using both audio and video information. First,...
Ziyou Xiong