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dc.contributor.authorJahre, Magnus
dc.contributor.authorMillet, Philippe
dc.date.accessioned2022-07-07T07:55:26Z
dc.date.available2022-07-07T07:55:26Z
dc.date.created2021-01-04T18:46:44Z
dc.date.issued2021
dc.identifier.isbn9783030535315
dc.identifier.urihttps://hdl.handle.net/11250/3003373
dc.description.abstractEmbedded image processing systems face stringent and conflicting constraints which commonly result in developers overly specialising systems to the problem-at-hand. In other words, they give priority to efficiency, which is an immediate concern, over the longer term development cost reduction benefits of building reusable components. In this paper, we present the foundational TULIPP Reference Platform (TRP) which enables making domain-specific generality versus specificity trade-offs through the definition of TRP instances. Each TRP instance includes the key software and hardware components for a given domain as well as productivity-enhancing components if these can be accommodated within the typical constraints of the domain. While TRP instances primarily enable intra-domain reuse, they also enable inter-domain reuse as collections of components used in one instance may be straightforwardly reused in other instances. At present, TRP instances are defined for the space, medical, automotive, robotics, and Unmanned Aerial Vehicle (UAV) domains.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofTowards Ubiquitous Low-power Image Processing Platforms
dc.titleTRP: A Foundational Platform for High-Performance Low-Power Embedded Image Processingen_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber15-31en_US
dc.identifier.doi10.1007/978-3-030-53532-2_2
dc.identifier.cristin1865184
dc.relation.projectEC/H2020/688403en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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