Machine learning methods for low-cost pollen monitoring – Model optimisation and interpretability

Mills, Sophie A.; Maya-Manzano, José M.; Tummon, Fiona; MacKenzie, A. Rob; Pope, Francis D.

doi:10.1016/j.scitotenv.2023.165853

Science of The Total Environment

2023

DOI: 10.1016/j.scitotenv.2023.165853

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Machine learning methods for low-cost pollen monitoring – Model optimisation and interpretability

Sophie A. Mills,

José M. Maya-Manzano,

Fiona Tummon

et al.

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Machine learning methods for low-cost pollen monitoring – Model optimisation and interpretability

Cited by 2 publications

References 41 publications

DeepPollenCount: a swin-transformer-YOLOv5-based deep learning method for pollen counting in various plant species

DeepPollenCount: a swin-transformer-YOLOv5-based deep learning method for pollen counting in various plant species

Detection of a biological aerosol using optical particle counters

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