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IJCAI-ECAI 2026Demonstrations Track

SoilNet App: AI-Assisted Expert-level Annotations of Soil Horizons

Vipin Singh, Joey Pruessing, Teodor Chiaburu, Einar Eberhardt, Sina Hesse, Stefan Broda, Frank Haußer, Felix Biessmann

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摘要

Precise descriptions of soil horizons are required for policy makers, agriculture and many applications in civil engineering. Up to date correct soil horizon annotations require human experts as they follow complex hierarchical taxonomies. We present the SoilNet App, a web-based demonstrator that guides experts through relevant tasks for expert-level soil horizon annotations from soil profile images. To demonstrate the reliability of the SoilNet app we present results of a user study with soil horizon annotation experts, which highlights the difficulty of image-only-based annotation and suggests that collaborating with our model not only increases expert performance but also improves inter-annotator consistency. Our app is publicly accessible (https://soilnet.demo.calgo-lab.de).