Thomas O’Shea Wheller: VespAI: Applying Deep Learning to the Detection of Invasive Hornets

Based at the University of Exeter, Thomas worsk with honey bees, bumble bees, and a variety of other social insects to improve colony health and resilience. His current research includes projects pertaining to honey bee epidemiology and Varroa resistance, bumble bee ecology, and the detection of invasive hornets using artificial intelligence (AI).
The invasive Asian hornet, Vespa velutina nigrithorax, has spread rapidly across large areas of Europe and East Asia, raising concern due to its impacts on beekeeping, agriculture, and biodiversity. To date, authorities have struggled to contain the hornets, as colonies must be detected and destroyed early in the invasion curve if establishment is to be prevented. There is a pressing need to develop improved monitoring technologies within a limited timeframe. In this talk, I outline VespAI, an automated system for the rapid detection of V. velutina.