research-article

Accelerators for biologically-inspired attention and recognition

Authors:

Chuanjun Zhang,

Michael DeBole,

Srinidhi KesturAuthors Info & Claims

DAC '13: Proceedings of the 50th Annual Design Automation Conference

Article No.: 135, Pages 1 - 6

https://doi.org/10.1145/2463209.2488900

Published: 29 May 2013 Publication History

Abstract

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.

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Cited By

Yang XYan JWang WLi SHu BLin J(2022)Brain-inspired models for visual object recognition: an overviewArtificial Intelligence Review10.1007/s10462-021-10130-z55:7(5263-5311)Online publication date: 10-Jan-2022
https://doi.org/10.1007/s10462-021-10130-z
Pantho MBhowmik PBobda C(2019)Neuromorphic Image Sensor Design with Region-Aware Processing2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2019.00089(459-464)Online publication date: Jul-2019
https://doi.org/10.1109/ISVLSI.2019.00089
Pantho MBhowmik PBobda C(2018)Pixel-Parallel Architecture for Neuromorphic Smart Image Sensor with Visual Attention2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2018.00053(245-250)Online publication date: Jul-2018
https://doi.org/10.1109/ISVLSI.2018.00053
Show More Cited By

Index Terms

Accelerators for biologically-inspired attention and recognition
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

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Published In

cover image ACM Conferences

DAC '13: Proceedings of the 50th Annual Design Automation Conference

May 2013

1285 pages

ISBN:9781450320719

DOI:10.1145/2463209

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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EDAC: Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CEDA

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SIGBED: ACM Special Interest Group on Embedded Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 May 2013

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DAC '13

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DAC '13: The 50th Annual Design Automation Conference 2013

May 29 - June 7, 2013

Texas, Austin

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Cited By

Yang XYan JWang WLi SHu BLin J(2022)Brain-inspired models for visual object recognition: an overviewArtificial Intelligence Review10.1007/s10462-021-10130-z55:7(5263-5311)Online publication date: 10-Jan-2022
https://doi.org/10.1007/s10462-021-10130-z
Pantho MBhowmik PBobda C(2019)Neuromorphic Image Sensor Design with Region-Aware Processing2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2019.00089(459-464)Online publication date: Jul-2019
https://doi.org/10.1109/ISVLSI.2019.00089
Pantho MBhowmik PBobda C(2018)Pixel-Parallel Architecture for Neuromorphic Smart Image Sensor with Visual Attention2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)10.1109/ISVLSI.2018.00053(245-250)Online publication date: Jul-2018
https://doi.org/10.1109/ISVLSI.2018.00053
Bhowmik PPantho MAsadinia MBobda C(2018)Design of a Reconfigurable 3D Pixel-Parallel Neuromorphic Architecture for Smart Image Sensor2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2018.00110(786-7868)Online publication date: Jun-2018
https://doi.org/10.1109/CVPRW.2018.00110
Eldridge SWaterland ASeltzer MAppavoo JJoshi A(2015)Towards General-Purpose Neural Network ComputingProceedings of the 2015 International Conference on Parallel Architecture and Compilation (PACT)10.1109/PACT.2015.21(99-112)Online publication date: 18-Oct-2015
https://dl.acm.org/doi/10.1109/PACT.2015.21

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