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    CDC
    2008
    IEEE
    98views Control Systems» more  CDC 2008»
    Equivalence between Approximate Dynamic Inversion and Proportional-Integral control
    14 years 2 months ago
    Equivalence between Approximate Dynamic Inversion and Proportional-Integral control
    Download  www.dtic.mil
    —Approximate Dynamic Inversion (ADI) has been established as a method to control minimum-phase, nonaffine-incontrol systems. Previous results have shown that for single-input no...
    Justin Teo, Jonathan P. How
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    ISBI
    2008
    IEEE
    109views Medical Imaging» more  ISBI 2008»
    Segmentation of the evolving left ventricle by learning the dynamics
    14 years 8 months ago
    Segmentation of the evolving left ventricle by learning the dynamics
    Download  people.sabanciuniv.edu
    We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learn...
    Walter Sun, Müjdat Çetin, Raymond Chan...
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    TMI
    2008
    138views more  TMI 2008»
    Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
    13 years 7 months ago
    Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
    Download  ntur.lib.ntu.edu.tw
    A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
    Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
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    ICML
    2006
    IEEE
    143views Machine Learning» more  ICML 2006»
    Efficient inference on sequence segmentation models
    14 years 8 months ago
    Efficient inference on sequence segmentation models
    Download  www.it.iitb.ac.in
    Sequence segmentation is a flexible and highly accurate mechanism for modeling several applications. Inference on segmentation models involves dynamic programming computations tha...
    Sunita Sarawagi
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    CIRA
    2007
    IEEE
    179views Robotics» more  CIRA 2007»
    Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
    14 years 2 months ago
    Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
    Download  www.cs.cmu.edu
    — Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
    Yang Gu, Manuela M. Veloso
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