Articles | Volume 41, issue 2
https://doi.org/10.5194/jm-41-165-2022
© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
04 Nov 2022
Research article |
| 04 Nov 2022
| 04 Nov 2022
Artificial intelligence applied to the classification of eight middle Eocene species of the genus Podocyrtis (polycystine radiolaria)
Related authors
Clim. Past, 21, 1431–1441, 2025
Biogeosciences, 22, 3029–3046, 2025
Biogeosciences, 22, 1929–1946, 2025
Clim. Past, 20, 2629–2644, 2024
Cited articles
Aitchison, J. C., Suzuki, N., Caridroit, M., Danelian, T., and Noble, P.:
Paleozoic radiolarian biostratigraphy, in: Catalogue of Paleozoic Radiolarian Genera, edited by: Danelian, T., Caridroit, M., Noble,
P., and Aitchison, J. C., Geodiversitas, Vol. 39, 503–531, Scientific
Publications of the Muséum National d'Histoire Naturelle, Paris, https://doi.org/10.5252/g2017n3a5, 2017.
Beaufort, L. and Dollfus, D.: Automatic recognition of coccoliths by
dynamical neural networks, Mar. Micropaleontol., 51, 57–73, https://doi.org/10.1016/j.marmicro.2003.09.003, 2004.
Beaufort, L., de Garidel Thoron, T., Mix, A. C., and Pisias, N. G.: ENSO-like
forcing on Oceanic Primary Production during the late Pleistocene, Science,
293, 2440–2444, https://doi.org/10.1126/science.293.5539.2440, 2001.
Brocher, J.: biovoxxel/BioVoxxel-Toolbox: BioVoxxel Toolbox (v2.5.3),
Zenodo, https://doi.org/10.5281/zenodo.5986129, 2022.
Carlsson, V.: Podocyrtis Image Dataset, Recherche Data Gouv [data set], https://doi.org/10.57745/G7CHQL,
2022.
