2026-05-30T07:06:15Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/287732026-02-03T11:33:15Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Chaves García, Antonio Jesús author Martín-Fernández, Cristian author Llopis-Torres, Luis Manuel author Díaz-Rodríguez, Manuel author Ruiz-Mata, Rocío author Gálvez-Montañez, Enrique de author Recio-Criado, María Marta author Trigo-Pérez, María del Mar author Picornell Rodríguez, Antonio author 2023-12-20 Airborne pollen is produced by plants for their sexual reproduction and can have negative impacts on public health. The current monitoring systems are based on manual sampling processes which are tedious and time-consuming. Due to that, pollen concentrations are often reported with a delay of up to one week. In this study, we present an open-source user-friendly web application powered by deep learning for automatic pollen count and classification. The application aims to simplify the process for non-IT users to count and classify different types of pollen, reducing the effort required compared to manual methods. To overcome the challenges of acquiring large labelled datasets, we propose a semi-automatic labelling approach, which combines human expertise and machine learning techniques. The results demonstrate that our approach significantly reduces the effort required for users to count and classify pollen taxa accurately. The model achieved high precision and recall rates (> 96% mAP@0.5), enabling reliable pollen identification and prediction. Chaves, A.J., Martín, C., Torres, L.L. et al. Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis. Earth Sci Inform (2023). https://doi.org/10.1007/s12145-023-01189-z https://hdl.handle.net/10630/28773 10.1007/s12145-023-01189-z Informática - Aplicaciones Polen - Dispersión Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis