Selecting the most suitable activation function is a critical factor in the effectiveness of deep
learning models, as it influences their learning capacity, stability, and computational …

Early detection of damage in the support structure (submerged part) of an offshore wind
turbine is crucial as it can help to prevent emergency shutdowns and extend the lifespan of …

Compared with other forms of cancer, gastric cancer has high mortality and incidence rates,
making it a major cause of death worldwide. Accurate diagnosis is crucial in the treatment of …

The recognition performance deteriorates if degradation factors including blur, noise, and
non-uniform illumination exist in the image when acquiring a finger-vein image. Especially …

As a booming research area in the past decade, deep learning technologies have been
driven by big data collected and processed on an unprecedented scale. However, privacy …

Introduction The field of electroencephalogram (EEG)-based emotion identification has
received significant attention and has been widely utilized in both human-computer …

Introduction The precise identification of retinal disorders is of utmost importance in the
prevention of both temporary and permanent visual impairment. Prior research has yielded …

We proposed an optimisation algorithm based on the sequence-to-sequence (Seq2Seq)
stacking of the gate recurrent unit (GRU) model to characterise and approximate the forward …

Neural operators extend data-driven models to map between infinite-dimensional functional
spaces. These models have successfully solved continuous dynamical systems represented …

This study explores multivariate time series forecasting, centering on the transformer model.
It examines the shortcomings of other predictive models like Recurrent Neural Networks …