Speakers
Mrs
Tessa Basso
(GAP)
Michael Tran
Description
The measurement of pathogens in field samples with in-lab microscopy produces massive amount of images (spores $\sim 5 – 30 \mu$m and scanned surface $\sim 3 $cm$^2$) whose analysis requires some automation. A trained AI-model of instance segmentation aims to recognize spores within images containing a multitude of other particles of similar sizes and/or displaying analogous textures.
Conversely, a device has been developed to capture airborne particles in the field and, based on their distinctive holographic patterns, the presence of spores of interest is estimated through an AI-model for object detection.
Primary authors
Co-authors
Mrs
Sara Leoni
(GAP)
Dr
Pierre-Henri Dubuis
(agroscope)
Dr
Sylvain Schnee
(Agroscope)
François Fleuret
(University of Geneva)
