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

Kang, Xiaochen, Lin, Xiangguo (2014) Graph-Based Divide and Conquer Method for Parallelizing Spatial Operations on Vector Data. Remote Sensing, 6 (10). doi:10.3390/rs61010107

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleGraph-Based Divide and Conquer Method for Parallelizing Spatial Operations on Vector Data
JournalRemote Sensing
AuthorsKang, XiaochenAuthor
Lin, XiangguoAuthor
Year2014 (October 22)Volume6
Issue10
PublisherMDPI AG
DOIdoi:10.3390/rs61010107Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17804911Long-form Identifiermindat:1:5:17804911:9
GUID0
Full ReferenceKang, Xiaochen, Lin, Xiangguo (2014) Graph-Based Divide and Conquer Method for Parallelizing Spatial Operations on Vector Data. Remote Sensing, 6 (10). doi:10.3390/rs61010107
Plain TextKang, Xiaochen, Lin, Xiangguo (2014) Graph-Based Divide and Conquer Method for Parallelizing Spatial Operations on Vector Data. Remote Sensing, 6 (10). doi:10.3390/rs61010107
In(2014, October) Remote Sensing Vol. 6 (10). MDPI AG

See Also

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

Kang, Xiaochen, Liu, Jiping, Lin, Xiangguo (2014) Streaming Progressive TIN Densification Filter for Airborne LiDAR Point Clouds Using Multi-Core Architectures. Remote Sensing, 6 (8). doi:10.3390/rs6087212
Zhang, Jixian, Duan, Minyan, Yan, Qin, Lin, Xiangguo (2014) Automatic Vehicle Extraction from Airborne LiDAR Data Using an Object-Based Point Cloud Analysis Method. Remote Sensing, 6 (9). doi:10.3390/rs6098405
Dong, Weihua, Li, Xian'en, Lin, Xiangguo, Li, Zhilin (2014) A Bidimensional Empirical Mode Decomposition Method for Fusion of Multispectral and Panchromatic Remote Sensing Images. Remote Sensing, 6 (9). doi:10.3390/rs6098446
Lin, Xiangguo, Zhang, Jixian (2014) Segmentation-Based Filtering of Airborne LiDAR Point Clouds by Progressive Densification of Terrain Segments. Remote Sensing, 6 (2). doi:10.3390/rs6021294
Feng, Jie, Wang, Lin, Yu, Haipeng, Jiao, Licheng, Zhang, Xiangrong (2019) Divide-and-Conquer Dual-Architecture Convolutional Neural Network for Classification of Hyperspectral Images. Remote Sensing, 11 (5). doi:10.3390/rs11050484
Zhao, Ming, An, Bowen, Wu, Yongpeng, Lin, Changqing (2013) Bi-SOGC: A Graph Matching Approach Based on Bilateral KNN Spatial Orders Around Geometric Centers for Remote Sensing Image Registration. IEEE Geoscience and Remote Sensing Letters, 10 (6) 1429-1433 doi:10.1109/lgrs.2013.2259612
Lu, Tingting, Ming, Dongping, Lin, Xiangguo, Hong, Zhaoli, Bai, Xueding, Fang, Ju (2018) Detecting Building Edges from High Spatial Resolution Remote Sensing Imagery Using Richer Convolution Features Network. Remote Sensing, 10 (9). doi:10.3390/rs10091496
Zhao, Qiao, Wang, Zengping, Li, Guomin, Liu, Xuanjun, Wang, Yuxuan (2023) A Fault Section Location Method for Distribution Networks Based on Divide-and-Conquer. Applied Sciences, 13 (10) 5974 doi:10.3390/app13105974
Wang, Qingdong, Yan, Li, Zhang, Li, Ai, Haibin, Lin, Xiangguo (2016) A Semantic Modelling Framework-Based Method for Building Reconstruction from Point Clouds. Remote Sensing, 8 (9). doi:10.3390/rs8090737
Chen, Hao, Shi, Zhenwei (2020) A Spatial-Temporal Attention-Based Method and a New Dataset for Remote Sensing Image Change Detection. Remote Sensing, 12 (10). doi:10.3390/rs12101662
Wang, Meilin, Song, Yexing, Wei, Pengxu, Xian, Xiaoyu, Shi, Yukai, Lin, Liang (2024) IDF-CR: Iterative Diffusion Process for Divide-and-Conquer Cloud Removal in Remote-Sensing Images. IEEE Transactions on Geoscience and Remote Sensing, 62. 1-14 doi:10.1109/tgrs.2024.3378720
 
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 Β© 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: August 25, 2025 14:53:13
Go to top of page