<div class="csl-bib-body">
<div class="csl-entry">Pratheepkumar, A., Ikeda, M., Pichler, A., & Vincze, M. (2024). Towards Robotic 3D Surface Processing with Global Local Neural Region Descriptor Fields. In <i>European Robotics Forum 2024</i> (pp. 218–223). Springer. https://doi.org/10.34726/8403</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/209760
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dc.identifier.uri
https://doi.org/10.34726/8403
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dc.description.abstract
Although great progress has been made in the field of AI re- cently with regard to robot assisted manufacturing, there are still major hurdles to overcome before cognitive robots learn processes from humans and execute them independently. Recent developments show one-shot re- gion of interest knowledge transfer across category level objects by the application of implicit neural networks. This work extends the current state of the art with a hybrid global-local approach to feature extraction and documents the first practical application of this technology.
en
dc.language.iso
en
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dc.relation.ispartofseries
Springer Proceedings in Advanced Robotics
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Robotics
en
dc.subject
process optimization
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dc.subject
Object Recognition
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dc.title
Towards Robotic 3D Surface Processing with Global Local Neural Region Descriptor Fields
