Junior research group Data Science in Agriculture
In agricultural production processes, data is ubiquitous. Sensor data recorded by machines, aerial or satellite images, data about weather and climate conditions, yields and soil properties together provide a rich and detailed source of information about many aspects of agricultural production processes. Exploiting these large amounts of data by modern data science methods is a promising direction to both gain novel knowledge about these processes and to optimize process parameters, leading to more efficient and sustainable production.
The junior research group Data Science in Agriculture studies intelligent data analysis methods and their application in agricultural science and engineering. A focus of our work is to develop machine learning methods that are specifically tailored to the statistical properties of data stemming from agricultural production processes. On the application side, we currently focus on pattern recognition problems in precision farming for crop and livestock production.
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Sept 17-20, 2019
Trainingschool on measuring and modelling gaseous emissions from livestock systems, ATB Potsdam
The FRUTIC Symposium 2019: Innovations in Pre- and Postharvest Supply Chain of...
The INSECTA 2019 International Conference aims to give an overview of...
Sept 17-20, 2019: Trainingschool on measuring and modelling gaseous emissions from livestock systems, Potsdam
The interdisciplinary training school provides hands-on training in measuring...
22. Aug. 2019: In Anwesenheit von Brandenburgs Wissenschaftsministerin Dr....
6. Juni 2019: Brandenburgs Agrar- und Umweltstaatssekretärin Dr. Carolin...
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