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BMCBI
2010
214views more  BMCBI 2010»
15 years 2 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
CVIU
2006
162views more  CVIU 2006»
15 years 1 months ago
Unsupervised scene analysis: A hidden Markov model approach
This paper presents a new approach to scene analysis, which aims at extracting structured information from a video sequence using directly low-level data. The method models the se...
Manuele Bicego, Marco Cristani, Vittorio Murino
CVPR
1998
IEEE
16 years 4 months ago
Subtly Different Facial Expression Recognition and Expression Intensity Estimation
We have developed a computer vision system, including both facial feature extraction and recognition, that automatically discriminates among subtly different facial expressions. E...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...
MASCOTS
2003
15 years 3 months ago
Derivation of Passage-time Densities in PEPA Models using ipc: the Imperial PEPA Compiler
We present a technique for defining and extracting passage-time densities from high-level stochastic process algebra models. Our high-level formalism is PEPA, a popular Markovian...
Jeremy T. Bradley, Nicholas J. Dingle, Stephen T. ...
RAS
2000
187views more  RAS 2000»
15 years 1 months ago
Detection, tracking, and classification of action units in facial expression
Most of the current work on automated facial expression analysis attempt to recognize a small set of prototypic expressions, such as joy and fear. Such prototypic expressions, how...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...