The key to addressing these challenges lies in separating the encoder and decoder components of multimodal machine learning models.

2025 年3月，狄耐克脑电波交互事业部一行前往厦门大学“脑认知与智能计算实验室”开展参观交流活动。此次受邀参观，是狄耐克在推动脑电波交互技术实际应用进程中的重要探索，加速相关技术在睡眠健康领域的创新与发展。

To solve abovementioned problems, a novel deep learning based spatio-temporal graph convolutional neural network (STGCN) is developed for intelligent fault diagnosis of wind turbines in this paper.

Frontotemporal dementia also called FTD, is a rarer type of dementia caused by a build up of proteins, tau, FUS and TDP-43, in the frontal and temporal lobes of the brain. Dementia is caused by ...

Inspired by the recent Retentive Network (RetNet), we develop a novel convolutional retentive network for EEG decoding (RetEEG), which integrates temporal priors into the self-attention mechanism to ...