Vote for your favorite mineral in #MinCup25! - Chrysotile vs. Pectolite
Two new minerals to launch this year's cup! Hazardous (but useful!) chrysotile faces off against stunning gem pectolite.
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

Qureshi, Rizwan, Uzair, Muhammad, Khurshid, Khurram, Yan, Hong (2019) Hyperspectral document image processing: Applications, challenges and future prospects. Pattern Recognition, 90. 12-22 doi:10.1016/j.patcog.2019.01.026

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleHyperspectral document image processing: Applications, challenges and future prospects
JournalPattern Recognition
AuthorsQureshi, RizwanAuthor
Uzair, MuhammadAuthor
Khurshid, KhurramAuthor
Yan, HongAuthor
Year2019 (June)Volume90
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2019.01.026Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9367730Long-form Identifiermindat:1:5:9367730:3
GUID0
Full ReferenceQureshi, Rizwan, Uzair, Muhammad, Khurshid, Khurram, Yan, Hong (2019) Hyperspectral document image processing: Applications, challenges and future prospects. Pattern Recognition, 90. 12-22 doi:10.1016/j.patcog.2019.01.026
Plain TextQureshi, Rizwan, Uzair, Muhammad, Khurshid, Khurram, Yan, Hong (2019) Hyperspectral document image processing: Applications, challenges and future prospects. Pattern Recognition, 90. 12-22 doi:10.1016/j.patcog.2019.01.026
In(2019) Pattern Recognition Vol. 90. Elsevier BV

See Also

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

, Zia-ul-Haque, Qureshi, Rizwan, Nawaz, Mehmood, Yar, Faheem, Tunio, Nazish, Uzair, Muhammad (2019) Analysis of ECG Signal Processing and Filtering Algorithms. International Journal of Advanced Computer Science and Applications, 10. doi:10.14569/ijacsa.2019.0100370
Khurshid, Khurram, Faure, Claudie, Vincent, Nicole (2012) Word spotting in historical printed documents using shape and sequence comparisons. Pattern Recognition, 45 (7). 2598-2609 doi:10.1016/j.patcog.2011.10.013
Zahra, Asmat, Perwaiz, Nazia, Shahzad, Muhammad, Fraz, Muhammad Moazam (2023) Person re-identification: A retrospective on domain specific open challenges and future trends. Pattern Recognition, 142. 109669 doi:10.1016/j.patcog.2023.109669
Calvo-Zaragoza, Jorge, Gallego, Antonio-Javier (2019) A selectional auto-encoder approach for document image binarization. Pattern Recognition, 86. 37-47 doi:10.1016/j.patcog.2018.08.011
Zhe, Xuefei, Chen, Shifeng, Yan, Hong (2019) Directional statistics-based deep metric learning for image classification and retrieval. Pattern Recognition, 93. 113-123 doi:10.1016/j.patcog.2019.04.005
Kang, Seokjun, Iwana, Brian Kenji, Uchida, Seiichi (2021) Complex image processing with less data—Document image binarization by integrating multiple pre-trained U-Net modules. Pattern Recognition, 109. 107577pp. doi:10.1016/j.patcog.2020.107577
Lu, Tan, Dooms, Ann (2021) Probabilistic homogeneity for document image segmentation. Pattern Recognition, 109. 107591pp. doi:10.1016/j.patcog.2020.107591
Vincent, Nicole, Ogier, Jean-Marc (2019) Shall deep learning be the mandatory future of document analysis problems?. Pattern Recognition, 86. 281-289 doi:10.1016/j.patcog.2018.09.010
Ren, Yan, Kong, Adams Wai Kin, Jiao, Licheng (2020) A survey on image and video cosegmentation: Methods, challenges and analyses. Pattern Recognition, 103. 107297pp. doi:10.1016/j.patcog.2020.107297
Matiz, Sergio, Barner, Kenneth E. (2019) Inductive conformal predictor for convolutional neural networks: Applications to active learning for image classification. Pattern Recognition, 90. 172-182 doi:10.1016/j.patcog.2019.01.035
Stamatopoulos, Nikolaos, Gatos, Basilis, Perantonis, Stavros J. (2009) A method for combining complementary techniques for document image segmentation. Pattern Recognition, 42 (12). 3158-3168 doi:10.1016/j.patcog.2008.10.020
 
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 1, 2025 01:28:48
Go to top of page