Handling irregularly sampled signals with gated temporal convolutional networks

Article Engineering, Electrical & Electronic

Forecasting of medical equipment demand and outbreak spreading based on deep long short-term memory network: the COVID-19 pandemic in Turkey

Erdinc Koc et al.

Summary: The outbreak of COVID-19 has led to an increased demand for healthcare equipment, and forecasting these demands using AI-based models can effectively predict the amount needed. This study presents a deep model approach based on a multilayer long short-term memory network for forecasting medical equipment demand and outbreak spreading during the COVID-19 pandemic.

SIGNAL IMAGE AND VIDEO PROCESSING (2022)

添加到收藏夹

Article Engineering, Electrical & Electronic

Iterative missing data recovery algorithm for non-stationary signals

Nabeel Ali Khan et al.

Summary: This paper proposes an algorithm to reconstruct missing samples from non-stationary signals. The algorithm estimates the instantaneous frequencies and time-varying amplitudes to recover the complete signal. Research results show that this method provides more accurate estimates compared to existing techniques.

SIGNAL IMAGE AND VIDEO PROCESSING (2022)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Gated temporal convolutional neural network and expert features for diagnosing and explaining physiological time series: A case study on heart rates

Shenda Hong et al.

Summary: This paper introduces a novel deep learning method TEG-net, which combines different neural network models to accurately diagnose and explain physiological time series data, achieving significant experimental results. This method can improve diagnostic accuracy while providing intuitive explanations.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

添加到收藏夹

Article Environmental Sciences