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

Titel:	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
Sprache:	Englisch
Autorenschaft:	Tiedemann, Tim Lange, Timo Meyer, Philipp Keppner, Matthis
Erscheinungsdatum:	Okt-2023
Ist Ergänzung zu:	https://drive.google.com/drive/folders/1VZdogs0yVqrjzXGfrBSlqFP_ZkaAL66P
Projekt:	Robotik in der Landwirtschaft
Konferenz:	International Conference on Intelligent Robots and Systems 2023
URI:	http://hdl.handle.net/20.500.12738/15393
DOI:	10.48441/4427.1504
Begutachtungsstatus:	Diese Version hat ein Peer-Review-Verfahren durchlaufen (Peer Review)
Einrichtung:	Forschungs- und Transferzentrum Smart Systems Department Informatik Fakultät Technik und Informatik
Dokumenttyp:	Poster
Hinweise zur Quelle:	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.
Enthalten in den Sammlungen:	Publications with full text

Datei	Beschreibung	Größe	Format
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	Öffnen/Anzeigen