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dc.contributor.authorYıldız, Nerhunen_US
dc.contributor.authorCesur, Evrenen_US
dc.contributor.authorTavşanoğlu, Ahmet Vedaten_US
dc.date.accessioned2019-06-27T18:28:36Z
dc.date.available2019-06-27T18:28:36Z
dc.date.issued2014
dc.identifier.citationYıldız, N., Cesur, E. & Tavşanoğlu, A. V. (2014). Design of a third generation real-time cellular neural network emulator. Paper presented at the 2014 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA), 1-2. doi:10.1109/CNNA.2014.6888621en_US
dc.identifier.isbn9781479960071
dc.identifier.issn2165-0179
dc.identifier.issn2165-0152
dc.identifier.issn2165-0144
dc.identifier.urihttps://hdl.handle.net/11729/1635
dc.identifier.urihttp://dx.doi.org/10.1109/CNNA.2014.6888621
dc.description.abstractIn this paper, the features of the next generation Real-Time Cellular Neural Network Processor (RTCNNP-v3) are discussed. The RTCNNP-v2 structure is the only CNN implementation that is reported to be capable of processing full-HD 1080p@60 (1920 x 1080 resolution at 60 Hz frame rate) video images in real-time, due to its fully-pipelined architecture, however, it has some weaknesses like the inability to divide the processing in spatial domain, record and recall intermediate results to an external memory and has some issues in its internal memory coding. Those shortcomings are to be addressed in the next design of our CNN emulator - RTCNNP-v3, which will increase the range of applications and enable the implementation to match the requirements of the cutting-edge movie production technologies like UHD (4K) and the future FUHD (8K).en_US
dc.description.sponsorshipThis study was supported by The Scientific and Technological Research Council of Turkey (TOBITAK) under project number 108E023en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/CNNA.2014.6888621
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCellular neural networksen_US
dc.subjectField programmable gate arraysen_US
dc.subjectNext generation networkingen_US
dc.subjectEducational institutionsen_US
dc.subjectComputed tomographyen_US
dc.subjectArraysen_US
dc.subjectCellular neural netsen_US
dc.subjectImage resolutionen_US
dc.subjectNext generation networksen_US
dc.subjectPipeline processingen_US
dc.subjectReal-time systemsen_US
dc.subjectVideo signal processingen_US
dc.subjectThird-generation real-time cellular neural network emulator designen_US
dc.subjectNext generation real-time cellular neural network processoren_US
dc.subjectRTCNNP-v3 structureen_US
dc.subjectRTCNNP-v2 structureen_US
dc.subjectCNN implementationen_US
dc.subjectFull-HD video image processingen_US
dc.subjectPipelined architectureen_US
dc.subjectSpatial domainen_US
dc.subjectExternal memoryen_US
dc.subjectInternal memory codingen_US
dc.subjectMovie production technologiesen_US
dc.subjectFUHDen_US
dc.titleDesign of a third generation real-time cellular neural network emulatoren_US
dc.typeconferenceObjecten_US
dc.description.versionPublisher's Versionen_US
dc.relation.journal2014 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA)en_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.contributor.authorID0000-0001-8590-1518
dc.identifier.startpage1
dc.identifier.endpage2
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorTavşanoğlu, Ahmet Vedaten_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.description.wosidWOS:000346574800031


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