Cognitive Weeding: An Approach to Single-Plant Specific Weed Regulation
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Published:2023-12
Issue:2-4
Volume:37
Page:175-181
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ISSN:0933-1875
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Container-title:KI - Künstliche Intelligenz
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language:en
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Short-container-title:Künstl Intell
Author:
Niemeyer MarkORCID, Renz MarianORCID, Pukrop MarenORCID, Hagemann DavidORCID, Zurheide Tim, Di Marco Daniel, Höferlin Markus, Stark Philipp, Rahe Florian, Igelbrink Matthias, Jenz Mario, Jarmer ThomasORCID, Trautz Dieter, Stiene Stefan, Hertzberg JoachimORCID
Abstract
AbstractThis paper provides a comprehensive overview of the architecture required to implement selective weeding in arable farming, as developed within the Cognitive Weeding project. This end-to-end architecture begins with data acquisition utilizing drones, robots, or agricultural machinery, followed by data management, AI-based data annotation, knowledge-based inference to determine the necessary treatment, resulting in an application map for selective hoeing. The paper meticulously details the various components of the architecture and illustrates through examples how they are interconnected.
Funder
Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI)
Publisher
Springer Science and Business Media LLC
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1. AI in Current and Future Agriculture;KI - Künstliche Intelligenz;2023-12
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