Detail publikace

Automatic image analysis applied to the recognition of quartz surface microtextures using neural network

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

10

URL

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"
}