• DocumentCode
    1699770
  • Title

    A 54GOPS 51.8mW analog-digital mixed mode Neural Perception Engine for fast object detection

  • Author

    Kim, Minsu ; Kim, Joo-Young ; Lee, Seungjin ; Oh, Jinwook ; Yoo, Hoi-Jun

  • Author_Institution
    Dept. of Electron. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
  • fYear
    2009
  • Firstpage
    649
  • Lastpage
    652
  • Abstract
    A mixed mode Neural Perception Engine (NPE) is proposed as the pre-processing accelerator of multi-object recognition processor to reduce the computational complexity and increase its efficiency. It consists of Motion Estimator (ME), Visual Attention Engine (VAE) and Object Detection Engine (ODE). The fabricated chip achieves 54 GOPS 51.8 mW NPE. By implementing a fast and robust neuro-fuzzy algorithm in analog-digital mixed circuits, the area and power of the ODE is reduced by 59% and 44%, respectively, compared to those of all digital implementation. The NPE can increase the frame rate by 2.09x and reduce power consumption by 38% of the multi-object recognition processor.
  • Keywords
    fuzzy neural nets; image recognition; microprocessor chips; mixed analogue-digital integrated circuits; object detection; analog-digital mixed circuits; analog-digital mixed mode neural perception engine; computational complexity; fast object detection; motion estimator; multiobject recognition processor; neurofuzzy algorithm; object detection engine; preprocessing accelerator; visual attention engine; Analog circuits; Analog-digital conversion; Energy consumption; Engines; Heuristic algorithms; Laboratories; Motion estimation; Object detection; Object recognition; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Custom Integrated Circuits Conference, 2009. CICC '09. IEEE
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-4071-9
  • Electronic_ISBN
    978-1-4244-4073-3
  • Type

    conf

  • DOI
    10.1109/CICC.2009.5280749
  • Filename
    5280749