Stories

The INNOSETA project has come to an end. An overview is given of how the project has tried to bridge the innovation gap between research and developers of spraying technologies and end users.

Within this project, together with the flax sector, Inagro, VITO and ILVO, a digital, visual tool for monitoring the crop position of flax is being developed.

This project combines the potential of artificial intelligence with the use of camera technology for site-specific weed detection.

Within this project, a prototype of a robot and corresponding implements will be developed in co-creation with farmers and mechatronics companies.

An inspection system was demonstrated for classifying different types of minced meat.

The power of artificial intelligence in computer vision was demonstrated.

By using a linear moving setup and a hyperspectral NIR camera with regression model, volume ratios of mixtures of dry herbs were calculated.

The demand for rapid detection methods that can be applied on the production line is growing fast. In the framework of the VLAIO Vlevavlees project, some methods were tested for their applicability at...

Vision inspection (RGB, multispectral, hyperspectral) can be used to automate processes or quality control or to improve traceability.

Filter

Collect and disseminate innovative spraying techniques

Satellite images as a tool for monitoring of flax plots

AI4Agriculture

CIMAT

In-line, non-contact distinction between pork, veal, beef, chicken, and lamb mince

Machine learning (AI) for classifying peppers

Determination of volume ratios of dry spice mixtures

Spectral measuring methods for fresh meat

Living Lab Agrifood 4.0