Vote for your favorite mineral in #MinCup25! - Baryte vs. Hematite
It's a heavyweight match between industrial powerhouses as soft #baryte competes against rusty red #hematite.
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

Di Nardo, Emanuel, Ciaramella, Angelo (2023) Tracking vision transformer with class and regression tokens. Information Sciences, 619. 276-287 doi:10.1016/j.ins.2022.11.055

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleTracking vision transformer with class and regression tokens
JournalInformation Sciences
AuthorsDi Nardo, EmanuelAuthor
Ciaramella, AngeloAuthor
Year2023 (January)Volume619
PublisherElsevier BV
DOIdoi:10.1016/j.ins.2022.11.055Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID15511362Long-form Identifiermindat:1:5:15511362:8
GUID0
Full ReferenceDi Nardo, Emanuel, Ciaramella, Angelo (2023) Tracking vision transformer with class and regression tokens. Information Sciences, 619. 276-287 doi:10.1016/j.ins.2022.11.055
Plain TextDi Nardo, Emanuel, Ciaramella, Angelo (2023) Tracking vision transformer with class and regression tokens. Information Sciences, 619. 276-287 doi:10.1016/j.ins.2022.11.055
In(2023) Information Sciences Vol. 619. Elsevier BV

See Also

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

Liu, Chang, Hirota, Kaoru, Dai, Yaping (2023) Patch attention convolutional vision transformer for facial expression recognition with occlusion. Information Sciences, 619. 781-794 doi:10.1016/j.ins.2022.11.068
Wang, Zheng, Liu, Jiali (2023) Reinforcement learning based-adaptive tracking control for a class of semi-markov non-Lipschitz uncertain system with unmatched disturbances. Information Sciences, 626. 407-427 doi:10.1016/j.ins.2023.01.043
Zhang, Jianwei, Wang, Jingchao, Zhang, Huanlong, Miao, Mengen, Zhang, Jie, Wu, Di (2023) Exploiting spatial and temporal context for online tracking with improved transformer. Image and Vision Computing, 133. 104672 doi:10.1016/j.imavis.2023.104672
Chen, Xuanchi, Zheng, Xiangwei, Sun, Kai, Liu, Weilong, Zhang, Yuang (2023) Self-supervised vision transformer-based few-shot learning for facial expression recognition. Information Sciences, 634. 206-226 doi:10.1016/j.ins.2023.03.105
Liu, Lei, Yen, Gary G., He, Zhenan (2025) EvolutionViT: Multi-objective evolutionary vision transformer pruning under resource constraints. Information Sciences, 689. doi:10.1016/j.ins.2024.121406
Del Corso, Gianna M., Romani, Francesco (2016) A multi-class approach for ranking graph nodes: Models and experiments with incomplete data. Information Sciences, 329. 619-637 doi:10.1016/j.ins.2015.09.046
Zhou, Yao, Yi, Zhang, Yen, Gary G. (2025) Efficient fine-tuning of vision transformer via path-augmented parameter adaptation. Information Sciences, 703. doi:10.1016/j.ins.2025.121948
Di Lena, Pietro, Margara, Luciano (2014) Nondeterministic Cellular Automata. Information Sciences, 287. 13-25 doi:10.1016/j.ins.2014.07.007
Park, Jinseong, Choi, Yujin, Byun, Junyoung, Lee, Jaewook, Park, Saerom (2023) Efficient differentially private kernel support vector classifier for multi-class classification. Information Sciences, 619. 889-907 doi:10.1016/j.ins.2022.10.075
Lu, Jianglin, Wang, Hailing, Zhou, Jie, Yan, Mengfan, Wen, Jiajun (2022) Deep asymmetric hashing with dual semantic regression and class structure quantization. Information Sciences, 589. 235-249 doi:10.1016/j.ins.2021.12.112
Veloso de Melo, Vinícius, Banzhaf, Wolfgang (2018) Automatic feature engineering for regression models with machine learning: An evolutionary computation and statistics hybrid. Information Sciences, 430. 287-313 doi:10.1016/j.ins.2017.11.041
 
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 19, 2025 00:51:07
Go to top of page