Partner: ULLMANNA s.r.o.

field: AGRICULTURE

Colleagues from the Advanced Data Analysis and Simulation Lab led by Jan Martinovič have participated in a unique project of Ullmann. This company is developing an agricultural weeding machine that will enable in-line weed control by recognising the target crop using machine learning. This will lead to farming activities without the use of chemical sprays.

Within this project, machine learning was employed to automatically identify crops, in this case sugar beet, from weeds. Thus, a neural network was designed and trained for this task.  Crop recognition will allow the weeding machine to remove the weeds while not damaging the crop grown. Due to the direct deployment directly on the weeding machine, additional requirements are placed on the resulting technology regarding the HW used and the recognition speed.

The project was supported within the framework of the support tool “Digital Innovation Hub Ostrava” combining the activities of IT4Innovations and MSIC Ostrava, which enables small and medium-sized companies to assess and possibly address their needs in the field of digitalization.

PARTNER´S NOTE

Martin Ullmann
Chief Executive Officer, Co-founder, Ullmanna

“Our intended product has a significant positive impact on the environment and society - it enables an increase in food production without the use of pesticides that negatively affect both the environment and human health.”

This success story was supported by the EuroCC project. This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 951732. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Germany, Bulgaria, Austria, Croatia, Cyprus, the Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, the United Kingdom, France, the Netherlands, Belgium, Luxembourg, Slovakia, Norway, Switzerland, Turkey, Republic of North Macedonia, Iceland, Montenegro. This project has received funding from the Ministry of Education, Youth and Sports of the Czech Republic (ID:MC2101).