Automatic detection of airborne pollen: an overview

J Buters, B Clot, C Galán, R Gehrig, S Gilge, F Hentges… - Aerobiologia, 2024 - Springer
Pollen monitoring has traditionally been carried out using manual methods first developed in
the early 1950s. Although this technique has been recently standardised, it suffers from …

Honey authentication: A review of the issues and challenges associated with honey adulteration

D Bose, M Padmavati - Food Bioscience, 2024 - Elsevier
Honey, often referred to as' liquid gold,'a time-honoured natural food with a rich history, has
now ascended to the status of a superfood in today's global market, thanks to its myriad …

Gray-level invariant Haralick texture features

T Löfstedt, P Brynolfsson, T Asklund, T Nyholm… - PloS one, 2019 - journals.plos.org
Haralick texture features are common texture descriptors in image analysis. To compute the
Haralick features, the image gray-levels are reduced, a process called quantization. The …

Automatic and online pollen monitoring

J Oteros, G Pusch, I Weichenmeier… - International archives of …, 2015 - karger.com
Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all
operated manually. To date, automated pollen monitoring has only been feasible in areas …

Pollen analysis using multispectral imaging flow cytometry and deep learning

S Dunker, E Motivans, D Rakosy, D Boho… - New …, 2021 - Wiley Online Library
Pollen identification and quantification are crucial but challenging tasks in addressing a
variety of evolutionary and ecological questions (pollination, paleobotany), but also for other …

Precise automatic classification of 46 different pollen types with convolutional neural networks

V Sevillano, K Holt, JL Aznarte - Plos one, 2020 - journals.plos.org
In palynology, the visual classification of pollen grains from different species is a hard task
which is usually tackled by human operators using microscopes. Many industries, including …

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry

CM Barnes, AL Power, DG Barber, RK Tennant… - New …, 2023 - Wiley Online Library
Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global
scales. Palynology is typically performed manually by microscopic analysis; a specialised …

Automatic taxonomic identification based on the Fossil Image Dataset (> 415,000 images) and deep convolutional neural networks

X Liu, S Jiang, R Wu, W Shu, J Hou, Y Sun, J Sun… - Paleobiology, 2023 - cambridge.org
The rapid and accurate taxonomic identification of fossils is of great significance in
paleontology, biostratigraphy, and other fields. However, taxonomic identification is often …

Automatic identification of fossils and abiotic grains during carbonate microfacies analysis using deep convolutional neural networks

X Liu, H Song - Sedimentary Geology, 2020 - Elsevier
Petrographic analysis based on microfacies identification in thin sections is widely used in
sedimentary environment interpretation and paleoecological reconstruction. Fossil …

Identification of pollen taxa by different microscopy techniques

M Pospiech, Z Javůrková, P Hrabec, P Štarha… - PLoS …, 2021 - journals.plos.org
Melissopalynology is an important analytical method to identify botanical origin of honey.
Pollen grain recognition is commonly performed by visual inspection by a trained person. An …