DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Meisel, Andreas | - |
dc.contributor.author | Stößel, Felix | - |
dc.date.accessioned | 2024-04-26T10:27:37Z | - |
dc.date.available | 2024-04-26T10:27:37Z | - |
dc.date.created | 2021-09-04 | - |
dc.date.issued | 2024-04-26 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12738/15636 | - |
dc.description.abstract | Die Objekterkennung ermöglicht Anwendungen im Bereich der Kollisionserkennung bei autonomen Fahrzeugen und Robotern. Diese Arbeit zeigt das Training eines neuronalen Faltungsnetzwerkes auf Daten des Open-Images- und COCO-Datensatzes. Das in dieser Arbeit trainierte YOLO-Netzwerk wird auf einem NVIDIA Jetson Nano im Darknet Framework getestet. | de |
dc.description.abstract | Object detection enables applications in the field of collision detection for autonomous vehicles and robots. This work shows the training of a convolutional neural network on data of the Open-Images- and COCO-dataset. The YOLO-network trained in this work will be tested in the Darknet Framework on the NVIDIA Jetson Nano. | en |
dc.language.iso | de | en_US |
dc.subject | Neuronale Faltungsnetzwerke | en_US |
dc.subject | Objekterkennung | en_US |
dc.subject | NVIDIA Jetson Nano | en_US |
dc.subject | YOLO | en_US |
dc.subject | COCO | en_US |
dc.subject | Open Images | en_US |
dc.subject | Darknet | en_US |
dc.subject | Training von neuronalen Netzen | en_US |
dc.subject | Convolutional Neural Networks | en_US |
dc.subject | object detection | en_US |
dc.subject | training of neural networks | en_US |
dc.subject.ddc | 004: Informatik | en_US |
dc.title | Neuronale Indoor-Objekterkennung für mobile Roboter | de |
dc.type | Thesis | en_US |
openaire.rights | info:eu-repo/semantics/openAccess | en_US |
thesis.grantor.department | Fakultät Technik und Informatik | en_US |
thesis.grantor.department | Department Informatik | en_US |
thesis.grantor.universityOrInstitution | Hochschule für Angewandte Wissenschaften Hamburg | en_US |
tuhh.contributor.referee | Tiedemann, Tim | - |
tuhh.identifier.urn | urn:nbn:de:gbv:18302-reposit-185212 | - |
tuhh.oai.show | true | en_US |
tuhh.publication.institute | Fakultät Technik und Informatik | en_US |
tuhh.publication.institute | Department Informatik | en_US |
tuhh.type.opus | Bachelor Thesis | - |
dc.type.casrai | Supervised Student Publication | - |
dc.type.dini | bachelorThesis | - |
dc.type.driver | bachelorThesis | - |
dc.type.status | info:eu-repo/semantics/publishedVersion | en_US |
dc.type.thesis | bachelorThesis | en_US |
dcterms.DCMIType | Text | - |
tuhh.dnb.status | domain | en_US |
item.advisorGND | Meisel, Andreas | - |
item.creatorGND | Stößel, Felix | - |
item.languageiso639-1 | de | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
item.creatorOrcid | Stößel, Felix | - |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
item.openairetype | Thesis | - |
Appears in Collections: | Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
BA_Indoor-Objekterkennung_mobile Roboter.pdf | 21.52 MB | Adobe PDF | View/Open |
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