Artificial intelligence (AI) plays a more and more important role in our everyday life due to the
advantages that it brings when used, such as 24/7 availability, a very low percentage of …

Allergic diseases and asthma are intrinsically linked to the environment we live in and to
patterns of exposure. The integrated approach to understanding the effects of exposures on …

The identification of floral visitation by pollinators provides an opportunity to improve our
understanding of the fine-scale ecological interactions between plants and pollinators …

Airborne pollen monitoring is of global socio-economic importance as it provides information
on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has …

Airborne pollen monitoring has been an arduous task, making ecological applications and
allergy management virtually disconnected from everyday practice. Over the last decade …

Objective: In aerobiological monitoring and agriculture there is a pressing need for accurate,
label-free and automated analysis of pollen grains, in order to reduce the cost, workload and …

The main objective of this work is to use convolutional neural networks (CNN) to improve the
performance in previous works on their baseline for pollen grain classification, by improving …

Pollen identification is necessary for several subfields of geology, ecology, and evolutionary
biology. However, the existing methods for pollen identification are laborious, time …

Research on plant-pollinator interactions requires a diversity of perspectives and
approaches, and documenting changing pollinator-plant interactions due to declining insect …

Deep learning has gained significant popularity due to its exceptional performance in
various machine learning and artificial intelligence applications. In this paper, we propose a …