Robotics and Automation for agriculture and forestry.
- Collecting images with different sensors in real context and its annotation with phenotypic characteristics relevant to the agronomic process. - Create image datasets to test and validate neural networks for robots applied in forestry and agriculture. - Establish causal relationships between phenotypic characteristics derived from images and useful attributes for the agronomic process. - Validate robotics solutions for agriculture in a real context.
MSc in Agronomy
Minimum profile required
Proven experience in using deep learning algorithms for precision agriculture context applications.The jury may not award the scholarship if the quality of the candidates is inferior to that intended.
Experience in writing scientific articles Knowledge in image processing Availability for advanced training at the PhD level
Since 27 Dec 2021 to 11 Jan 2022
Cluster / Centre
Industrial and Systems Engineering / Robotics in Industry and Intelligent Systems