Pollen allergies are a cause of much suffering in an increasing number of individuals. Current pollen monitoring techniques are lacking due to their reliance on manual counting of pollen by human technicians. In this study, we present a neural network architecture capable of distinguishing pollen species using data from an automated particle measurement device. This study presents an improvement over the current state-of-the-art in the task of automated pollen classification using the fluorescence spectrum of aerosol particles.