• DocumentCode
    3426753
  • Title

    [Front cover]

  • fYear
    2009
  • fDate
    March 30 2009-April 2 2009
  • Abstract
    The following topics are dealt with: self-learning sensor fusion system; object classification; memory efficient predictions; diesel engines; driver pose estimation; 3D time-of-flight sensor; driver´s style classification; jerk analysis; recurrent neural network training; mild hybrid electric vehicle; multi-sensor coverage analysis; aspect-dependent targets; vehicle stability control; robust lane detection; assembly ergonomics filters; injury risk operations; 3D lidar processing; FPGA implementation; automotive speech recognition; sound base control; autonomous helicopter; probabilistic alert procedure; mobile machine damage detection and prognostic health monitoring technique.
  • Keywords
    diesel engines; driver information systems; field programmable gate arrays; helicopters; hybrid electric vehicles; object detection; optical radar; pose estimation; probability; recurrent neural nets; sensor fusion; speech recognition; stability; 3D lidar processing; 3D time-of-flight sensor; FPGA implementation; aspect-dependent targets; assembly ergonomics filters; automotive speech recognition; autonomous helicopter; diesel engines; driver pose estimation; driver style classification; injury risk operations; jerk analysis; memory efficient predictions; mild hybrid electric vehicle; mobile machine damage detection; multisensor coverage analysis; object classification; probabilistic alert procedure; prognostic health monitoring technique; recurrent neural network training; robust lane detection; self-learning sensor fusion system; sound base control; vehicle stability control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Vehicles and Vehicular Systems, 2009. CIVVS '09. IEEE Workshop on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    978-1-4244-2770-3
  • Type

    conf

  • DOI
    10.1109/CIVVS.2009.4938712
  • Filename
    4938712