Towards ubiquitous semantic metaverse: Challenges, approaches, and opportunities
In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive
cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which …
cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which …
Transforming smart cities with spatial computing
Spatial methods have a rich history of reforming city infrastructure. For example, John
Snow's 1854 London Cholera map spurred cities to protect drinking water via sewer systems …
Snow's 1854 London Cholera map spurred cities to protect drinking water via sewer systems …
Covid-gan: Estimating human mobility responses to covid-19 pandemic through spatio-temporal conditional generative adversarial networks
The COVID-19 pandemic has posed grand challenges to policy makers, raising major social
conflicts between public health and economic resilience. Policies such as closure or reopen …
conflicts between public health and economic resilience. Policies such as closure or reopen …
Detecting spatial flow outliers in the presence of spatial autocorrelation
Spatial flow outlier (SFO) detection aims to discover spatial flows whose non-spatial attribute
values are significantly different from their neighborhoods. Different from spatial flow …
values are significantly different from their neighborhoods. Different from spatial flow …
Spatiotemporal data mining: A survey
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big
spatial and spatiotemporal data. They are used in various application domains such as …
spatial and spatiotemporal data. They are used in various application domains such as …
Covid-gan+: Estimating human mobility responses to covid-19 through spatio-temporal generative adversarial networks with enhanced features
Estimating human mobility responses to the large-scale spreading of the COVID-19
pandemic is crucial, since its significance guides policymakers to give Non-pharmaceutical …
pandemic is crucial, since its significance guides policymakers to give Non-pharmaceutical …
Transdisciplinary foundations of geospatial data science
Recent developments in data mining and machine learning approaches have brought lots of
excitement in providing solutions for challenging tasks (eg, computer vision). However …
excitement in providing solutions for challenging tasks (eg, computer vision). However …
Parallel grid-based colocation mining algorithms on GPUs for big spatial event data
Colocation patterns refer to subsets of spatial features whose instances are frequently
located together. Mining colocation patterns is important in many applications such as …
located together. Mining colocation patterns is important in many applications such as …
mcRPL: a general purpose parallel raster processing library on distributed heterogeneous architectures
Parallel computing on distributed heterogeneous architectures (eg computing clusters with
multiple CPUs and GPUs) can significantly improve the computational efficiency and …
multiple CPUs and GPUs) can significantly improve the computational efficiency and …