Vote for your favorite mineral in #MinCup25! - Stibnite vs. Perovskite
It's all about how minerals interact with humans as dramatic #stibnite faces off against futuristic #perovskite.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Koeshidayatullah, Ardiansyah, Ferreira-Chacua, Ivan, Li, Weichang (2023) Is attention all geosciences need? Advancing quantitative petrography with attention-based deep learning. Computers & Geosciences, 181. 105466 doi:10.1016/j.cageo.2023.105466

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleIs attention all geosciences need? Advancing quantitative petrography with attention-based deep learning
JournalComputers & Geosciences
AuthorsKoeshidayatullah, ArdiansyahAuthor
Ferreira-Chacua, IvanAuthor
Li, WeichangAuthor
Year2023 (December)Volume181
PublisherElsevier BV
DOIdoi:10.1016/j.cageo.2023.105466Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID16888510Long-form Identifiermindat:1:5:16888510:9
GUID0
Full ReferenceKoeshidayatullah, Ardiansyah, Ferreira-Chacua, Ivan, Li, Weichang (2023) Is attention all geosciences need? Advancing quantitative petrography with attention-based deep learning. Computers & Geosciences, 181. 105466 doi:10.1016/j.cageo.2023.105466
Plain TextKoeshidayatullah, Ardiansyah, Ferreira-Chacua, Ivan, Li, Weichang (2023) Is attention all geosciences need? Advancing quantitative petrography with attention-based deep learning. Computers & Geosciences, 181. 105466 doi:10.1016/j.cageo.2023.105466
In(2023) Computers & Geosciences Vol. 181. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Davy, Nandito, Waheed, Umair Bin, Koeshidayatullah, Ardiansyah, El-Husseiny, Ammar, Ayranci, Korhan, Harris, Nicholas B., Dong, Tian (2024) Leveraging automated deep learning (AutoDL) in geosciences. Computers & Geosciences, 188. 105600 doi:10.1016/j.cageo.2024.105600
Colombo, Daniele, Turkoglu, Ersan, Li, Weichang, Rovetta, Diego (2021) Coupled physics-deep learning inversion. Computers & Geosciences, 157. 104917 doi:10.1016/j.cageo.2021.104917
Xiang, Yanjin, Wang, Zhiliang, Song, Ziang, Huang, Rong, Song, Guojie, Min, Fan (2024) SeismicTransformer: An attention-based deep learning method for the simulation of seismic wavefields. Computers & Geosciences, 190. 105629 doi:10.1016/j.cageo.2024.105629
Ren, Anjing, Wu, Liang, Xu, Jianglong, Xing, Yanjie, Qiu, Qinjun, Xie, Zhong (2025) A deep learning method for 3D geological modeling using ET4DD with offset-attention mechanism. Computers & Geosciences, 200. doi:10.1016/j.cageo.2025.105929
Nie, Wenliang, Gu, Jiayi, Li, Bo, Wen, Xiaotao, Nie, Xiangfei (2025) Quantitative lithology prediction from seismic data using deep learning. Computers & Geosciences, 196. doi:10.1016/j.cageo.2024.105821
Wang, Zhihao, Brenning, Alexander (2023) Unsupervised active–transfer learning for automated landslide mapping. Computers & Geosciences, 181. 105457 doi:10.1016/j.cageo.2023.105457
Mallick, Rishav, Meade, Brendan J. (2025) Smooth slip is all you need: A singularity-free boundary element method for fault slip problems. Computers & Geosciences, 196. doi:10.1016/j.cageo.2024.105820
Naseer, Farhan, Kazei, Vladimir, Li, Weichang (2024) Understanding 3D seismic data visualization with C++, OpenGL and GLSL. Computers & Geosciences, 191. 105681 doi:10.1016/j.cageo.2024.105681
Li, Guohua, Choi, Yeji (2021) HPC cluster-based user-defined data integration platform for deep learning in geoscience applications. Computers & Geosciences, 155. 104868 doi:10.1016/j.cageo.2021.104868
Bansal, Kamakhya, Tripathi, Ashish Kumar (2024) Dual level attention based lightweight vision transformer for streambed land use change classification using remote sensing. Computers & Geosciences, 191. 105676 doi:10.1016/j.cageo.2024.105676
Shao, Pingping, Feng, Jun, Zhang, Pengcheng, Lu, Jiamin (2024) Interpretable spatial-temporal attention convolutional network for rainfall forecasting. Computers & Geosciences, 185. 105535 doi:10.1016/j.cageo.2024.105535
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 18, 2025 09:43:14
Go to top of page