From the 1 of 14 linked papers with an AI index.
14 papers
AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts
Niklas Grieger, Jannik Raskob, Siamak Mehrkanoon +1
AnySleep is a deep learning system that automatically stages sleep using EEG or EOG data at flexible time resolutions, and it works well across many clinical sites and electrode se…
Temporal Context Conditioning for Seasonality-Aware Precipitation Nowcasting of High-Intensity Rainfall
Gijs van Nieuwkoop, Siamak Mehrkanoon
Precipitation nowcasting is increasingly being approached with deep learning models that learn directly from recent radar observations. Although such models can efficiently capture…
Beyond MSE: Improving Precipitation Nowcasting with Multi-Quantile Regression
Gijs van Nieuwkoop, Siamak Mehrkanoon
Deep-learning precipitation nowcasting models are often optimized using pointwise losses such as mean squared error or mean absolute error, which can lead to overly smooth forecast…
From Sleep Staging to Spindle Detection: A Case Study on End-to-End Automated Sleep Analysis
Niklas Grieger, Siamak Mehrkanoon, Philipp Ritter +1
Automation of sleep analysis, including both macrostructural (sleep stages) and microstructural (e.g., sleep spindles) elements, promises to enable large-scale sleep studies and to…
A Diffusion-Contrastive Graph Neural Network with Virtual Nodes for Wind Nowcasting in Unobserved Regions
Jie Shi, Siamak Mehrkanoon
Accurate weather nowcasting remains one of the central challenges in atmospheric science, with critical implications for climate resilience, energy security, and disaster preparedn…
EEG-MFTNet: An Enhanced EEGNet Architecture with Multi-Scale Temporal Convolutions and Transformer Fusion for Cross-Session Motor Imagery Decoding
Panagiotis Andrikopoulos, Siamak Mehrkanoon
Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices, providing critical support for individuals with motor impairments. However, acc…