The encoder employs stacked self-attention layers to capture spatial-temporal dependencies and thematic continuity, while the decoder leverages a two-stage attention mechanism combining multi-head ...

Therefore, this study attempts to build an injury risk prediction model using a combination of time-series image encoding and deep learning algorithms to address this issue better.

Analyzing time series data like EEG or MEG is challenging due to noisy, high-dimensional, and patient-specific signals. Deep learning methods have been demonstrated to be superior in analyzing time ...

Deep learning continues to offer groundbreaking technologies in communications systems just as it has in a variety of other fields. Despite the notable advancements of technologies based on DNN-based ...