DC FieldValueLanguage
dc.contributor.authorTiedemann, Tim-
dc.contributor.authorSchmidt, Anja-
dc.contributor.authorStricker, Jesse-
dc.contributor.authorFuhrmann, Jonas-
dc.date.accessioned2024-07-12T13:17:11Z-
dc.date.available2024-07-12T13:17:11Z-
dc.date.issued2024-07-01-
dc.identifier.isbn978-3-031-60023-4en_US
dc.identifier.isbn978-3-031-60022-7en_US
dc.identifier.issn1860-9503en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12738/16043-
dc.description.sponsorshipBundesministerium für Ernährung und Landwirtschaften_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofStudies in computational intelligenceen_US
dc.subject.ddc004: Informatiken_US
dc.titleFirst results of a comparison of machine learning hardware acceleration approaches using field programmable gate arrays in an agricultural mobile robotic application caseen
dc.typeinProceedingsen_US
dc.relation.conferenceInternational Symposium on Intelligent Distributed Computing 2023en_US
dc.description.versionPeerRevieweden_US
local.contributorPerson.editorKöhler-Bußmeier, Michael-
local.contributorPerson.editorRenz, Wolfgang-
local.contributorPerson.editorSudeikat, Jan-
tuhh.container.endpage39en_US
tuhh.container.startpage27en_US
tuhh.container.volume1138en_US
tuhh.oai.showtrueen_US
tuhh.publication.instituteDepartment Informatiken_US
tuhh.publication.instituteFakultät Technik und Informatiken_US
tuhh.publication.instituteForschungs- und Transferzentrum Smart Systemsen_US
tuhh.publisher.doi10.1007/978-3-031-60023-4_8-
tuhh.relation.ispartofseriesIntelligent Distributed Computing XVI : 16th International Symposium on Intelligent Distributed Computing, IDC 2023en_US
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)-
dc.relation.projectRobotik in der Landwirtschaften_US
dc.type.casraiConference Paper-
dc.type.dinicontributionToPeriodical-
dc.type.drivercontributionToPeriodical-
dc.type.statusinfo:eu-repo/semantics/publishedVersionen_US
dcterms.DCMITypeText-
local.comment.externalFunded by the Federal Ministry of Food and Agriculture (BMEL) by a decision of the German Bundestag. The Federal Offce for Agriculture and Food (BLE) provides coordinating support for artificial intelligence (AI) in agriculture as funding organization, grant number 28DK103C20.en_US
item.seriesrefIntelligent Distributed Computing XVI : 16th International Symposium on Intelligent Distributed Computing, IDC 2023-
item.tuhhseriesidIntelligent Distributed Computing XVI : 16th International Symposium on Intelligent Distributed Computing, IDC 2023-
item.creatorGNDTiedemann, Tim-
item.creatorGNDSchmidt, Anja-
item.creatorGNDStricker, Jesse-
item.creatorGNDFuhrmann, Jonas-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.creatorOrcidTiedemann, Tim-
item.creatorOrcidSchmidt, Anja-
item.creatorOrcidStricker, Jesse-
item.creatorOrcidFuhrmann, Jonas-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeinProceedings-
crisitem.author.deptDepartment Informatik-
crisitem.author.parentorgFakultät Technik und Informatik-
crisitem.project.funderBundesministerium für Ernährung und Landwirtschaft-
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