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Detecting the world's most accurate field boundaries

Project description

Detection algorithms for precision agriculture services

Accurate field boundaries and seeded acres are instrumental in precision agriculture services. However, inaccurate cadastral field boundary data lead to wrong critical decisions affecting the entire agricultural value chain. Norwegian start-up DigiFarm has developed a deep-resolution algorithm for Sentinel 2 imagery to increase image resolution by 10x, combined with a deep neural network model that automatically detects field boundaries and seeded acres to power precision agriculture. The EIC-funded CropCloud project will exploit the latest advancements in AI technology and super-resolution of satellite data to improve detection algorithms to achieve greater accuracy than the human eye, resulting in about 15 % higher accuracy than existing solutions.

Objective

DigiFarm detects the world’s most accurate field boundaries and seeded acres to power precision agriculture. Leveraging the latest advancements in Artificial Intelligence technology and super-resolution of Satellite data, our object detection algorithm achieves higher accuracy than the human eye, resulting in 12-15% higher accuracy than existing solutions.

Coordinator

DIGIFARM AS
Net EU contribution
€ 1 767 500,00
Address
HOLSETGATA 22
2317 HAMAR
Norway

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Norge Innlandet Innlandet
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 2 531 250,00