5 citations · 21 across the 28 of their papers we have counts for
6 papers · 1 filter
Deep coastal sea elements forecasting using U-Net based models
Jesús García Fernández, Ismail Alaoui Abdellaoui, Siamak Mehrkanoon
The supply and demand of energy is influenced by meteorological conditions. The relevance of accurate weather forecasts increases as the demand for renewable energy sources increas…
Deep multi-stations weather forecasting: explainable recurrent convolutional neural networks
Ismail Alaoui Abdellaoui, Siamak Mehrkanoon
Deep learning applied to weather forecasting has started gaining popularity because of the progress achieved by data-driven models. The present paper compares two different deep le…
Deep Neural-Kernel Machines
Siamak Mehrkanoon
In this chapter we review the main literature related to the recent advancement of deep neural-kernel architecture, an approach that seek the synergy between two powerful class of…
Wind speed prediction using multidimensional convolutional neural networks
Kevin Trebing, Siamak Mehrkanoon
Accurate wind speed forecasting is of great importance for many economic, business and management sectors. This paper introduces a new model based on convolutional neural networks…
Deep brain state classification of MEG data
Ismail Alaoui Abdellaoui, Jesus Garcia Fernandez, Caner Sahinli +1
Neuroimaging techniques have shown to be useful when studying the brain's activity. This paper uses Magnetoencephalography (MEG) data, provided by the Human Connectome Project (HCP…
SmaAt-UNet: Precipitation Nowcasting using a Small Attention-UNet Architecture
Kevin Trebing, Tomasz Stanczyk, Siamak Mehrkanoon
Weather forecasting is dominated by numerical weather prediction that tries to model accurately the physical properties of the atmosphere. A downside of numerical weather predictio…