Hardware-Accelerated Machine Vision using Field-Programmable Gate Arrays (FPGA)

dc.contributor.author Haughery, John
dc.contributor.author Noronha, Justin
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2018-02-18T03:46:21.000
dc.date.accessioned 2020-06-29T22:34:50Z
dc.date.available 2020-06-29T22:34:50Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2016
dc.date.embargo 2017-01-31
dc.date.issued 2016-01-01
dc.description.abstract <p>A hardware-accelerated vision system for object tracking was developed and implemented using FPGAs. Based on Amdahl’s Law equation, the final hardware design outperformed a similar software implementation by a factor of 7.7.</p>
dc.description.comments <p>The abstract, "Hardware-Accelerated Machine Vision using Field-Programmable Gate Arrays (FPGA)" (John R. Haughery and Jsutin E. Noronha), as published in the Proceedings of the ATMAE 2016 Conference (2016 ATMAE Annual Conference, Orlando, Florida, November 2–5, 2016)" is a copyrighted publication of ATMAE, the Association of Technology, Management, and Applied Engineering, 1390 Eisenhower Place, Ann Arbor, MI 48108 This paper has been republished with the authorization of ATMAE.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_conf/496/
dc.identifier.articleid 1500
dc.identifier.contextkey 9604468
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_conf/496
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/533
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_conf/496/2016_Haughery_ElectricityElectronics.pdf|||Sat Jan 15 00:30:40 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.title Hardware-Accelerated Machine Vision using Field-Programmable Gate Arrays (FPGA)
dc.type article
dc.type.genre abstract
dspace.entity.type Publication
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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