Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik
dc.contributor.author | Mitschke, Norbert | |
dc.date.accessioned | 2022-08-22T09:17:26Z | |
dc.date.available | 2022-08-22T09:17:26Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/58037 | |
dc.description.abstract | In 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. | en_US |
dc.language | German | en_US |
dc.relation.ispartofseries | Forschungsberichte aus der Industriellen Informationstechnik | en_US |
dc.subject.classification | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering | en_US |
dc.subject.other | künstliche neuronale Netze; Bildverarbeitung; bildbasierte Regelung; FPGA; CNN; image based visual servoing | en_US |
dc.title | Konvolutionäre neuronale Netze in der industriellen Bildverarbeitung und Robotik | en_US |
dc.type | book | |
oapen.identifier.doi | 10.5445/KSP/1000146397 | en_US |
oapen.relation.isPublishedBy | 44e29711-8d53-496b-85cc-3d10c9469be9 | en_US |
oapen.series.number | 26 | en_US |
oapen.pages | 212 | en_US |