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dc.contributor.authorMitschke, Norbert
dc.date.accessioned2022-08-23T04:02:12Z
dc.date.available2022-08-23T04:02:12Z
dc.date.issued2022
dc.date.submitted2022-08-22T09:17:26Z
dc.identifierhttps://library.oapen.org/handle/20.500.12657/58037
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/91407
dc.description.abstractIn the first part of this dissertation, a framework for the design of a CNN for FPGAs is presented, consisting of a preprocessing algorithm, an augmentation technique, a custom quantization scheme and a pruning step of the CNN. The combination of conventional image processing with neural networks is shown in the second part by an example from robotics, where an image-based visual servoing process is successfully conducted for a gripping process of a robot.
dc.languageGerman
dc.relation.ispartofseriesForschungsberichte aus der Industriellen Informationstechnik
dc.rightsopen access
dc.subject.otherkünstliche neuronale Netze; Bildverarbeitung; bildbasierte Regelung; FPGA; CNN; image based visual servoing
dc.subject.otherthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
dc.titleKonvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik
dc.typebook
oapen.identifier.doi10.5445/KSP/1000146397
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.pages212
dc.seriesnumber26


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