A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials
Crossref DOI link: https://doi.org/10.1038/s41598-022-16429-3
Published Online: 2022-09-28
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Genc, Arda
Kovarik, Libor
Fraser, Hamish L.
Text and Data Mining valid from 2022-09-28
Version of Record valid from 2022-09-28
Article History
Received: 28 February 2022
Accepted: 11 July 2022
First Online: 28 September 2022
Competing interests
: The authors declare no competing interests.