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dc.contributor.authorAfifi, SMen_NZ
dc.contributor.authorGholamhosseini, Hen_NZ
dc.contributor.authorPoopak, Sen_NZ
dc.date.accessioned2017-03-07T03:45:48Z
dc.date.available2017-03-07T03:45:48Z
dc.date.copyright2015-11en_NZ
dc.identifier.citationInternational Journal of Innovative Science, Engineering & Technology, vol.2(11), pp.733 - 752 (20)en_NZ
dc.identifier.issn2348-7968en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/10369
dc.description.abstractThe Support Vector Machine (SVM) is a common machine learning tool that is widely used because of its high classification accuracy . Implementing SVM for embedded real -time applications is very challenging because of the intensi ve computations required. This in creases the attractiveness of implementing SVM on hardware platforms for reaching high performance computing with low cost and power consumption. This paper provides the first comprehensive survey of current literature (2010- 2015) of different hardware implementation s of SVM classifier on Field -Programmable Gate Array (FPGA ). A classification of existing techniques is presented, along with a critical analysis and discussion . A challenging trade -off between meeting embedded real -time systems constraints and high classification accuracy has been observed. Finally , some key future research directions are suggested.
dc.publisherInternational Journal of Innovative Science Engineering and Technology (IJISET)
dc.relation.urihttp://ijiset.com/articlesv2/articlesv2s11.htmlen_NZ
dc.rightsThe authors confirms that “International Journal of Innovative Science, Engineering and Technology” and its Editors, Chief Editor, or reviewers can publish the article online as open access and authors grant permission to edit or alter the article if necessary.
dc.subjectSVM; FPGA; Hardware implementation; Embedded systems; Image processing
dc.titleHardware Implementations of SVM on FPGA: A State-of-the-Art Review of Current Practiceen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
aut.relation.endpage752
aut.relation.issue11en_NZ
aut.relation.pages20
aut.relation.startpage733
aut.relation.volume2en_NZ
pubs.elements-id196742


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