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    IDEAL
    2005
    Springer
    124views Intelligent Agents» more  IDEAL 2005»
    Predictive Vaccinology: Optimisation of Predictions Using Support Vector Machine Classifiers
    14 years 1 months ago
    Predictive Vaccinology: Optimisation of Predictions Using Support Vector Machine Classifiers
    Download  poincare.matf.bg.ac.rs
    Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidd...
    Ivana Bozic, Guanglan Zhang, Vladimir Brusic
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    EMNETS
    2007
    148views Sensor Networks» more  EMNETS 2007»
    An HMM framework for optimal sensor selection with applications to BSN sensor glove design
    13 years 11 months ago
    An HMM framework for optimal sensor selection with applications to BSN sensor glove design
    Download  www.doc.ic.ac.uk
    Laparoscopic surgical training is a challenging task due to the complexity of instrument control and demand on manual dexterity and hand-eye coordination. Currently, training and ...
    Rachel C. King, Louis Atallah, Ara Darzi, Guang-Zh...
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    TIT
    2008
    102views more  TIT 2008»
    On Low-Complexity Maximum-Likelihood Decoding of Convolutional Codes
    13 years 7 months ago
    On Low-Complexity Maximum-Likelihood Decoding of Convolutional Codes
    Download  www.engr.colostate.edu
    Abstract--This letter considers the average complexity of maximum-likelihood (ML) decoding of convolutional codes. ML decoding can be modeled as finding the most probable path take...
    Jie Luo
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    CSDA
    2011
    210views Social Sciences» more  CSDA 2011»
    Approximate forward-backward algorithm for a switching linear Gaussian model
    13 years 2 months ago
    Approximate forward-backward algorithm for a switching linear Gaussian model
    Download  www.math.ntnu.no
    Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
    Hugo Hammer, Håkon Tjelmeland
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    ECCV
    2008
    Springer
    182views Computer Vision» more  ECCV 2008»
    Learning for Optical Flow Using Stochastic Optimization
    14 years 9 months ago
    Learning for Optical Flow Using Stochastic Optimization
    Download  www.cs.cornell.edu
    Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
    Yunpeng Li, Daniel P. Huttenlocher
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