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https://doi.org/10.48441/4427.3090
| Publisher URL: | https://gil-net.de/Publikationen/GIL25_Proceedings_final_01.pdf | Publisher DOI: | 10.18420/giljt2025_38 | Title: | First results of combining RGB segments and multi-spectral pixel classes for strawberry ripeness detection | Language: | English | Authors: | Meyer, Philipp  Lange, Timo Trost, Matthis Tiedemann, Tim |
Editor: | Dörr, J. Steckel, T. Prankl, H. Kruder-Motsch, V. Bosse, S. Riegler-Nurscher, P. Floto, H. |
Other : | Gesellschaft für Informatik e.V. | Keywords: | strawberry harvesting; autonomous robot; multi-spectral imaging; machine learning | Issue Date: | 4-Feb-2025 | Part of Series: | Lecture Notes in Informatics (LNI)-Proceedings | Volume number: | P-385 | Journal or Series Name: | Lecture Notes in Informatics (LNI)-Proceedings | Startpage: | 333 | Endpage: | 338 | Project: | Robotik in der Landwirtschaft | Conference: | 45. GIL-Jahrestagung, Digitale Infrastrukturen für eine nachhaltige Land-, Forst-und Ernährungswirtschaft | Abstract: | Autonomous harvesting of strawberries is dependent on the detection of fruits and their ripeness. For harvesting in commercial fields, at least unripe, ripe, and overripe fruits must be distinguishable. In this paper, we employ visual image-wise segmentation with multi-spectral pixel-wise ripeness classification on real field recordings. Our results show the feasibility and potential of this combination. Furthermore, we identify problematic parts and necessary improvements. |
URI: | https://hdl.handle.net/20.500.12738/18604 | DOI: | 10.48441/4427.3090 | ISBN: | 978-3-88579-802-6 | ISSN: | 1617-5468 | Review status: | This version was peer reviewed (peer review) | Institute: | Fakultät Informatik und Digitale Gesellschaft | Type: | Chapter/Article (Proceedings) | Funded by: | Bundesministerium für Ernährung und Landwirtschaft |
| Appears in Collections: | Publications with full text |
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| Werner_2025_J._Phys.__Conf._Ser._3123_012026.pdf | 2.04 MB | Adobe PDF | View/Open |
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