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BMCBI
2005
89views more  BMCBI 2005»
13 years 8 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
ICASSP
2011
IEEE
13 years 16 days ago
Use of VTL-wise models in feature-mapping framework to achieve performance of multiple-background models in speaker verification
Recently, Multiple Background Models (M-BMs) [1, 2] have been shown to be useful in speaker verification, where the M-BMs are formed based on different Vocal Tract Lengths (VTLs)...
Achintya Kumar Sarkar, Srinivasan Umesh
ICIP
2000
IEEE
14 years 10 months ago
Hierarchical Image Probability (HIP) Models
We formulate a model for probability distributions on image spaces. We show that any distribution of images can be factored exactly into conditional distributions of feature vecto...
Clay Spence, Lucas C. Parra, Paul Sajda
ACIVS
2006
Springer
14 years 2 months ago
Discrete Choice Models for Static Facial Expression Recognition
In this paper we propose the use of Discrete Choice Analysis (DCA) for static facial expression classification. Facial expressions are described with expression descriptive units ...
Gianluca Antonini, Matteo Sorci, Michel Bierlaire,...
PODS
1991
ACM
98views Database» more  PODS 1991»
14 years 10 days ago
Minimum and Maximum Predicates in Logic Programming
A novel approach is proposed for ezpresaing and computing eficienily a large cla88 of problem8, including jinding the shortest path in a graph, that were previously considered imp...
Sumit Ganguly, Sergio Greco, Carlo Zaniolo