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Detail publikace
SIKORA, P. KIAC, M. COSTA, P. MOLINERO-GARCÍA, A. GORSKA, M.
Originální název
Automatic image analysis applied to the recognition of quartz surface microtextures using neural network
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
Microtextures imprinted on the surface of quartz grains provide in-depth information on the environmental conditions and sedimentary processes that affected the study sediments. Microtextural analyses are therefore widely used in the provenance studies of sediments. In order to minimize the subjectivity of microtextural recognition, we propose a new software, called DeepGrain (source codes are available at https://github.com/d eepgrains/deepgrain), for the automatic identification of microtextures on the surface of quartz grains using the DeepLabV3 model with applied improving techniques. The approach provides an accuracy of 99 % of the area of the tested grains and 63 % of the mechanical features on the surfaces of the tested grains. The inference of a single SEM image of quartz grain took an average of 3.10 sec, leading to a significant reduction in the analysis time of a single grain.
Klíčová slova
Artificial intelligence; Machine learning; Segmentation; SEM; Quartz microtextures; DeepGrain
Autoři
SIKORA, P.; KIAC, M.; COSTA, P.; MOLINERO-GARCÍA, A.; GORSKA, M.
Vydáno
24. 4. 2024
Nakladatel
PERGAMON-ELSEVIER SCIENCE LTD
Místo
OXFORD
ISSN
1878-4291
Periodikum
MICRON
Ročník
182
Číslo
July 2024
Stát
Spojené království Velké Británie a Severního Irska
Strany od
1
Strany do
10
Strany počet
URL
https://www.sciencedirect.com/science/article/pii/S0968432824000556?via%3Dihub
BibTex
@article{BUT188880, author="Pavel {Sikora} and Martin {Kiac} and Pedro J.M. {Costa} and Alberto {Molinero-García} and Martyna E. {Gorska}", title="Automatic image analysis applied to the recognition of quartz surface microtextures using neural network", journal="MICRON", year="2024", volume="182", number="July 2024", pages="1--10", doi="10.1016/j.micron.2024.103638", issn="1878-4291", url="https://www.sciencedirect.com/science/article/pii/S0968432824000556?via%3Dihub" }