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Hier finden Sie eine Auflistung der Publikation, welche im Rahmen von KI-iREPro veröffentlicht wurden:


Extreme Gradient Boosting for yield estimation compared with Deep Learning approaches

XComputers and Electronics in Agriculture, Volume 202, 2022

Florian Huber, Artem Yushchenko, Benedikt Stratmann, Volker Steinhage


Grouping Shapley Value Feature Importances of Random Forests for explainable Yield Prediction

IntelliSys 2024. LEcture Notes in Networks and Systems, vol. 824. Springer
Florian Huber, Hannes Engler, Anna Kicherer, KAtja Herzog, Reinhard Topfer, Volger Steinhage


Leveraging Remote Sensing Data for Yield Prediction with Deep Transfer Learning

MDPI Sensors 2024, 24, 770

Florian Huber*, Alvin Inderka*, Volker Steinhage (*authors with equal contribution)


Deep Interpolation of Remote Sensing Temperature Data with local Weather Stations and Partial Convolutions

Accepted at MDPI Sensors 2024

Florian Huber*, Stefan Schulz*, Volker Steinhage (*authors with equal contribution)

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