MARTIN - Deep Learning and Automation of Imaging-Based Quality of Seeds and Grains

ZZZZ Today, manual visual inspection of grain is still one of the most important quality assurance procedures throughout the value chain of bringing cereals from the field to the table. Together with FOSS, this project aims to develop and validate a method of automated image-based solutions that can replace subjective manual inspection and improve performance, robustness and consistency of the inspection. The method can potentially provide the grain industry with a disruptive new tool for ensuring quality and optimizing the value of agricultural commodities. Project period: 2020-2024 Budget: DKK 3,91 million