Vote for your favorite mineral in #MinCup25! - Taenite vs. Nontronite
It's a mineral found mostly in the farthest reaches of space vs one so common an exhaustive list of localities is nigh impossible as alloy #taenite faces off against clay #nontronite.
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

Ahmed, Moumen, Farag, Aly (2002) A neural approach to zoom-lens camera calibration from data with outliers. Image and Vision Computing, 20 (9). 619-630 doi:10.1016/s0262-8856(02)00051-3

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleA neural approach to zoom-lens camera calibration from data with outliers
JournalImage and Vision Computing
AuthorsAhmed, MoumenAuthor
Farag, AlyAuthor
Year2002 (August)Volume20
Issue9
PublisherElsevier BV
DOIdoi:10.1016/s0262-8856(02)00051-3Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID11232381Long-form Identifiermindat:1:5:11232381:7
GUID0
Full ReferenceAhmed, Moumen, Farag, Aly (2002) A neural approach to zoom-lens camera calibration from data with outliers. Image and Vision Computing, 20 (9). 619-630 doi:10.1016/s0262-8856(02)00051-3
Plain TextAhmed, Moumen, Farag, Aly (2002) A neural approach to zoom-lens camera calibration from data with outliers. Image and Vision Computing, 20 (9). 619-630 doi:10.1016/s0262-8856(02)00051-3
In(2002, August) Image and Vision Computing Vol. 20 (9) Elsevier BV

See Also

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

Sturm, Peter (1997) Self-calibration of a moving zoom-lens camera by pre-calibration. Image and Vision Computing, 15 (8). 583-589 doi:10.1016/s0262-8856(97)00015-2
Drummond, T., Cipolla, R. (2002) Real-time tracking of complex structures with on-line camera calibration. Image and Vision Computing, 20 (5). 427-433 doi:10.1016/s0262-8856(02)00013-6
Mirmehdi, Majid (2002) British Machine Vision Conference 2000. Image and Vision Computing, 20 (9). 595pp. doi:10.1016/s0262-8856(02)00048-3
Rother, Carsten (2002) A new approach to vanishing point detection in architectural environments. Image and Vision Computing, 20 (9). 647-655 doi:10.1016/s0262-8856(02)00054-9
(2002) Advert APM. Image and Vision Computing, 20 (3). doi:10.1016/s0262-8856(02)00029-x
(2002) Advert AMC. Image and Vision Computing, 20 (3). doi:10.1016/s0262-8856(02)00030-6
Ji, Qiang (2002) 3D Face pose estimation and tracking from a monocular camera. Image and Vision Computing, 20 (7). 499-511 doi:10.1016/s0262-8856(02)00024-0
(2002) Call for papers. Image and Vision Computing, 20 (2). 165pp. doi:10.1016/s0262-8856(02)00017-3
(2002) Call for Papers. Image and Vision Computing, 20 (3). 237pp. doi:10.1016/s0262-8856(02)00028-8
Kurugollu, Fatih, Sankur, Bülent, Emre Harmancı, A. (2002) Image segmentation by relaxation using constraint satisfaction neural network. Image and Vision Computing, 20 (7). 483-497 doi:10.1016/s0262-8856(02)00023-9
Garai, G, Chaudhuri, B.B (2002) Erratum to “A cascaded genetic algorithm for efficient optimization and pattern matching” [Image and Vision Computing 20(4) (2002) 265–277]. Image and Vision Computing, 20 (13). 1017-1019 doi:10.1016/s0262-8856(02)00123-3
 
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 15, 2025 17:38:21
Go to top of page