Accelerators for biologically-inspired attention and recognition

Mi Sun Park, Chuanjun Zhang, Michael Debole, Srinidhi Kestur, Vijaykrishnan Narayanan, Mary Jane Irwin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Video and image content has begun to play a growing role in many applications, ranging from video games to autonomous self-driving vehicles. In this paper, we present accelerators for gist-based scene recognition, saliency-based attention, and HMAX-based object recognition that have multiple uses and are based on the current understanding of the vision systems found in the visual cortex of the mammalian brain. By integrating them into a two-level hierarchical system, we improve recognition accuracy and reduce computational time. Results of our accelerator prototype on a multi-FPGA system show real-time performance and high recognition accuracy with large speedups over existing CPU, GPU and FPGA implementations.

Original languageEnglish (US)
Title of host publicationProceedings of the 50th Annual Design Automation Conference, DAC 2013
StatePublished - 2013
Event50th Annual Design Automation Conference, DAC 2013 - Austin, TX, United States
Duration: May 29 2013Jun 7 2013

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Other50th Annual Design Automation Conference, DAC 2013
Country/TerritoryUnited States
CityAustin, TX

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation


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