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Ein spannendes und abwechslungsreiches Programm rund um das Thema der
Künstlichen Intelligenz.
Das englischsprachige Symposium ist kostenlos und auch für externe Teilnehmer (ohne KI-Vorwissen) zugänglich. Geplant ist ein ganzer Tag mit verschiedenen Themen, die im weitesten Sinne mit KI und Lebenswissenschaften zu tun haben.
Mehr Informationen zum Programmablauf und der Registrierungs-Link in Kürze hier
Key Note: Dr. Martin Junghans, CTO Innovation Studios, IBM Deutschland GmbH |
| Nora Gourmelon, FAU Erlangen-Nürnberg AI-based Remote Sensing Applications What do bird populations, glaciers and water consumption have in common? We can monitor them using remote sensing. To reduce manual effort, AI-based methods are being developed to take over this task |
| Siming Bayer, FAU Erlangen-Nürnberg tba |
| Emanuel Jakobowsky, Technical University of Applied Sciences Ingolstadt Detecting and counting wheat spike heads from UAV-based images using deep convolutional neural networks Manual detection and counting of wheat head spikes is essential for maximizing wheat yields but this task is also time-consuming and subject to human error. This talk presents a plot-level analysis using a Mask R-CNN for automatic detection and counting of wheat spike heads on UAV-based images. |
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| Raphael Oefelein, HSWT Standort Triesdorf 3D Crop Modeling with Neural Radiance Fields and Hyperspectral Imaging for Vegetation Index Computation In today’s agricultural landscape, numerous complex challenges such as sustainable resource utilization, environmental impact mitigation, and the need for more efficient production methodologies have emerged. In this context, the creation of digital twins for crop plants presents new opportunities for agricultural digitization. Realistic simulations aim to assist farmers in basing their management practices on data-driven insights, optimizing resource utilization, while simultaneously minimizing environmental impacts1. The development of a lifelike 3D object stands as a pivotal step in the evolution of a comprehensive digital twin. |
| Andreas Gilson, Fraunhofer IIS Digitizing Reality: AI as a Key Ingredient in the Creation of a complex Digital Twin Digital Twins of real-world objects and processes continue to gain importance in various fields of application. A digital representation of a plant can be an invaluable asset for e.g. researchers and breeders and in the future also for producers. The ability to precisely capture the state of a plant at any time and analyze, assess and predict the phenotypic development - from architecture to fruit size – promises new insights. We describe the role of AI in the development of a digital twin of a cherry tree. |
| Dr. Sebastian Fritsch, HSWT Standort Triesdorf More than ChatGPT: The benefits of Large Language Models for agriculture |
| Prof. Dr. Dominik Grimm, HSWT Standort Straubing Advancing Protein Engineering with Large Language Models Accurate prediction of protein properties is an essential task in many areas of biotechnology, including enzyme engineering and protein-hybrid optoelectronics. In this talk, we will show the benefits of large language models for predicting protein thermophilicity and thermostability, and give an outlook on how these models will revolutionize the design of synthetic proteins. |