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CORDIS - EU research results
CORDIS

Accelerating the achievement of EU Green Deal Goals for pesticide and fertilizer reduction through AI, data and robotic technologies.

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Dissemination, communication and exploitation plan and reports v2 (opens in new window)

The main reference for communication activities with guidelines for partners to disseminate and exploit results Also includes an action plan on the planned liaisons with complementary AI Data and Robotics initiatives

Dissemination, communication and exploitation plan and reports v3 (opens in new window)

The main reference for communication activities, with guidelines for partners to disseminate and exploit results. Also includes an action plan on the planned liaisons with complementary AI, Data and Robotics initiatives.

Dissemination, communication and exploitation plan and reports v1 (opens in new window)

The main reference for communication activities with guidelines for partners to disseminate and exploit results Also includes an action plan on the planned liaisons with complementary AI Data and Robotics initiatives

Smart Droplets Academy - Program, Timeline & Activities v1 (opens in new window)

Work plan on training activities includes the production of learning kits and recorded video content

Reference Architectures and Resources Mapping (opens in new window)

Report on reference architectures, common resources and prospective links with other AI, Data and Robotics projects and initiatives

Industry Needs & Requirements Analysis v2 (opens in new window)

Assessment report on industry needs, incl. mapping of requirements and metrics/ KPIs that relate to the use case implementation. Output of T2.1, T2.2.

Industry Needs & Requirements Analysis v1 (opens in new window)

Assessment report on industry needs, incl. mapping of requirements and metrics/ KPIs that relate to the use case implementation. Output of T2.1, T2.2

Publications

Integrating processed-based models and machine learning for crop yield prediction (opens in new window)

Author(s): Michiel G.J. Kallenberg, Bernardo Maestrini, Ron van Bree, Paul Ravensbergen, Christos Pylianidis, Frits van Evert, Ioannis N. Athanasiadis
Published in: Workshop on Synergy of Scientific and Machine Learning Modeling, International Conference on Machine Learning, 2023, ISSN 2331-8422
Publisher: ArXiv.org
DOI: 10.48550/arXiv.2307.13466

Learning Long-Term Crop Management Strategies with CyclesGym

Author(s): Turchetta, Matteo; Corinzia, Luca; Sussex, Scott; Burton, Amanda; Herrera, Juan; Athanasiadis, Ioannis N.; Buhmann, Joachim M.; Krause, Andreas
Published in: ISBN: 9781713871088, 2022

Nitrogen management with reinforcement learning and crop growth models (opens in new window)

Author(s): Michiel G.J. Kallenberg, Hiske Overweg, Ron van Bree and Ioannis N. Athanasiadis
Published in: Environmental Data Science, 2023, ISSN 2634-4602
Publisher: Cambridge University Press.
DOI: 10.1017/eds.2023.28

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