Results 31 to 40 of about 4,357,372 (295)
Learned Spatial Data Partitioning
Proceedings of the Sixth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2023 Due to the significant increase in the size of spatial data, it is essential to use distributed parallel processing systems to efficiently analyze spatial data. In this paper, we first study learned spatial data partitioning, which effectively assigns groups of big spatial data to computers based on locations of data by using machine learning ...
Keizo Hori +4 more
openaire +2 more sources
Modelling count data with overdispersion and spatial effects [PDF]
, 2005 In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model
Czado, Claudia, Gschlößl, Susanne
core +4 more sources
Human Clustering Based on Graph Embedding and Space Functions of Trajectory Stay Points on Campus
Applied SciencesSpatial big data about human mobility have been employed intensively in understanding human spatial activity patterns, which is a central topic in many applications.
Ke Xie +4 more
doaj +1 more source
Spatial interpolation of high-frequency monitoring data
, 2009 Climate modelers generally require meteorological information on regular grids, but monitoring stations are, in practice, sited irregularly. Thus, there is a need to produce public data records that interpolate available data to a high density grid ...
Stein, Michael L.
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Rectangular Hierarchical Cartograms for Socio-Economic Data [PDF]
, 2010 We present rectangular hierarchical cartograms for mapping socio-economic data. These density-normalising cartograms size spatial units by population, increasing the ease with which data for densely populated areas can be visually resolved compared to ...
Aidan Slingsby +9 more
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Scene Classification of Remote Sensing Images Based on Saliency Dual Attention Residual Network
IEEE Access, 2020 Scene classification of high-resolution Remote Sensing Images (RSI) is one of basic challenges in RSI interpretation. Existing scene classification methods based on deep learning have achieved impressive performances.
Dongen Guo, Ying Xia, Xiaobo Luo
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Inferring spatial and signaling relationships between cells from single cell transcriptomic data. [PDF]
, 2020 Single-cell RNA sequencing (scRNA-seq) provides details for individual cells; however, crucial spatial information is often lost. We present SpaOTsc, a method relying on structured optimal transport to recover spatial properties of scRNA-seq data by ...
Cang, Zixuan, Nie, Qing
core
Identification of Property Boundaries Using an IFC-Based Cadastral Database
Land, 2021 Property boundaries have a significant importance in cadaster as they define the legal extent of the ownership rights. Among 3D data models, Industry Foundation Class (IFC) provides the potential capabilities for modelling property boundaries in a 3D ...
Maryam Barzegar +3 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Chemotherapy‐induced peripheral neuropathy remains a major complication in pediatric cancer, with disrupted somatosensory and nociceptive processing being a key aspect. This review synthesizes empirical studies on alterations in somatosensory and nociceptive processing in children and adolescents with cancer.
Julia Schweiger +4 more
wiley +1 more source
SCMDOT: Spatial Clustering with Multiple Density-Ordered Trees
ISPRS International Journal of Geo-Information, 2017 With the rapid explosion of information based on location, spatial clustering plays an increasingly significant role in this day and age as an important technique in geographical data analysis.
Xiaozhu Wu, Hong Jiang, Chongcheng Chen
doaj +1 more source