Stochastic super-resolution for downscaling time-evolving atmospheric fields with a generative adversarial network
Generative adversarial networks (GANs) have been recently adopted for super-resolution,
an application closely related to what is referred to as “downscaling” in the atmospheric …
an application closely related to what is referred to as “downscaling” in the atmospheric …
PFST-LSTM: A spatiotemporal LSTM model with pseudoflow prediction for precipitation nowcasting
Precipitation nowcasting is an important task, which can serve numerous applications such
as urban alert and transportation. Previous studies leverage convolutional recurrent neural …
as urban alert and transportation. Previous studies leverage convolutional recurrent neural …
An semg-controlled 3d game for rehabilitation therapies: Real-time time hand gesture recognition using deep learning techniques
In recent years the advances in Artificial Intelligence (AI) have been seen to play an
important role in human well-being, in particular enabling novel forms of human-computer …
important role in human well-being, in particular enabling novel forms of human-computer …
An energy-based generative adversarial forecaster for radar echo map extrapolation
Precipitation nowcasting is an important task in weather forecast. The key challenge of the
task lies at radar echo map extrapolation. Recent studies show that a convolutional recurrent …
task lies at radar echo map extrapolation. Recent studies show that a convolutional recurrent …
Regional rainfall prediction using support vector machine classification of large-scale precipitation maps
E Hussein, M Ghaziasgar… - 2020 IEEE 23rd …, 2020 - ieeexplore.ieee.org
Rainfall prediction helps planners anticipate potential social and economic impacts
produced by too much or too little rain. This research investigates a class-based approach to …
produced by too much or too little rain. This research investigates a class-based approach to …