Articles | Volume 16, issue 6
https://doi.org/10.5194/cp-16-2415-2020
https://doi.org/10.5194/cp-16-2415-2020
Technical note
 | 
02 Dec 2020
Technical note |  | 02 Dec 2020

Technical note: A new automated radiolarian image acquisition, stacking, processing, segmentation and identification workflow

Martin Tetard, Ross Marchant, Giuseppe Cortese, Yves Gally, Thibault de Garidel-Thoron, and Luc Beaufort

Viewed

Total article views: 2,108 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,317 731 60 2,108 87 50 46
  • HTML: 1,317
  • PDF: 731
  • XML: 60
  • Total: 2,108
  • Supplement: 87
  • BibTeX: 50
  • EndNote: 46
Views and downloads (calculated since 09 Jul 2020)
Cumulative views and downloads (calculated since 09 Jul 2020)

Viewed (geographical distribution)

Total article views: 2,108 (including HTML, PDF, and XML) Thereof 1,862 with geography defined and 246 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 27 Mar 2024
Download
Short summary
Radiolarians are marine micro-organisms that produce a siliceous shell that is preserved in the fossil record and can be used to reconstruct past climate variability. However, their study is only possible after a time-consuming manual selection of their shells from the sediment followed by their individual identification. Thus, we develop a new fully automated workflow consisting of microscopic radiolarian image acquisition, image processing and identification using artificial intelligence.