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Research-driven innovation

We remain a research-active organization that publishes our work and collaborate with academic institutions.


We are a team brought together by a shared background in academia. All of our founders hold a PhD and have spent years actively contributing to scientific research.

Research keeps us curious at AI Lab. We work closely with external partners, combining our background with the vision of other companies and institutions to build, learn, and innovate together.

Recent publications in AI Lab include

2026

DecimeterWeedMan: An open-source platform for sub-decimeter spot-spraying integrating AI-vision and spray dynamics modeling

Luca Ponti, Michael Søndergaard Nørbo Madsen, Søren Kelstrup Skovsen, Marco Gentili, and Rasmus Nyholm Jørgensen

Smart Agricultural Technology  ·  sciencedirect.com ↗

2026

Adapting a Globally-Trained Plant Identification Model for Multi-Species Detection of Invasive Alien Plants in Roadside Imagery

Goëau H, Espitalier V, Lombardo J-C, Botella C, Høye TT, Dyrmann M, Bonnet P, Joly A

Biodiversity Information Science and Standards  ·  biss.pensoft.net ↗

2025

Adapting a global plant identification model to detect invasive alien plant species in high-resolution road side images

Vincent Espitalier, Jean-Christophe Lombardo, Hervé Goëau, Christophe Botella, Toke Thomas Høye, Mads Dyrmann, Pierre Bonnet, Alexis Joly

Ecological Informatics 89  ·  sciencedirect.com ↗

2025

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

Pringle, Stephen, et al.

Nature Ecology & Evolution  ·  nature.com ↗

2024

High-speed camera system for efficient monitoring of invasive plant species along roadways

Dyrmann, Mads, et al.

F1000Research  ·  pmc.ncbi.nlm.nih.gov ↗

2024

Review of Crop Phenotyping in Field Plot Experiments Using UAV-Mounted Sensors and Algorithms

Tanaka, Takashi S. T., et al.

Drones  ·  mdpi.com ↗

2021

Camera-based estimation of sugar beet stem points and weed cover using convolutional neural networks

Dyrmann, Mads, et al.

Precision agriculture  ·  brill.com ↗

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