Intermediate results of a multi-spectral-imaging-based ripeness and malformed classification on an object- and pixel-basis using field programmable gate arrays for an autonomous strawberry-harvesting robot

Please use this identifier to cite or link to this item: https://doi.org/10.48441/4427.1504

Title:	Intermediate results of a multi-spectral-imaging-based ripeness and malformed classification on an object- and pixel-basis using field programmable gate arrays for an autonomous strawberry-harvesting robot
Language:	English
Authors:	Tiedemann, Tim Lange, Timo Meyer, Philipp Keppner, Matthis
Issue Date:	Oct-2023
Is supplement to:	https://drive.google.com/drive/folders/1VZdogs0yVqrjzXGfrBSlqFP_ZkaAL66P
Project:	Robotik in der Landwirtschaft
Conference:	International Conference on Intelligent Robots and Systems 2023
URI:	http://hdl.handle.net/20.500.12738/15393
DOI:	10.48441/4427.1504
Review status:	This version was peer reviewed (peer review)
Institute:	Forschungs- und Transferzentrum Smart Systems Department Informatik Fakultät Technik und Informatik
Type:	Poster
Additional note:	In: IEEE IROS 2023 Workshop on Agricultural Robotics for a Sustainable Future (WARS). Funded by the Federal Ministry of Food and Agriculture (BMEL) by a decision of the German Bundestag. The Federal Office for Agriculture and Food (BLE) provides coordinating support for artificial intelligence (AI) in agriculture as funding organization, grant number 28DK103C20.
Appears in Collections:	Publications with full text

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iros2023_tiedemann_et_al_RoLand_comp.pdf	Poster presented at IEEE IROS 2023 Workshop on Agricultural Robotics for a Sustainable Future, winner 3rd prize "Advancement in Robotic Farm Technology".	640.29 kB	Adobe PDF	View/Open