The approach combines scanning electron microscopy with a computer vision model and a web-based application to automatically classify pollen grains based on their microscopic surface features. Its ...

A team of researchers from the Smithsonian Tropical Research Institute is digitizing images of pollen from more than 18,000 plant species from the tropics. The work is published in the journal PLANTS, ...

Pollen analysis of halophytes is crucial for their accurate identification and taxonomic classification within respective families. This study aimed to highlight the systematic pollen analysis of 15 ...

Pollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models with a focus on deep learning, have an ...

A team of researchers from the Smithsonian Tropical Research Institute is digitizing images of pollen from more than18,000 plant species from the tropics. These images are being used to train a ...

Pollen from 18,000 tropical plants was digitized in Panama. The images will be used to train a machine-learning model to identify pollen grains, as part of the PollenGEO project Elisabeth King A team ...