… We summarize deep learning techniques for BCI applications. To our best knowledge, we …
Deep learning models for BCI. • We provide guidelines for choosing a suitable deep learning …

… algorithms to the newer methods of deep learning. We explore two different types … deep
learning methods, namely, convolutional neural networks (CNN) and recurrent neural networks (…

… for a single-layer neural network; the architecture of neural networks is becoming better with
… , we use deep neural networks which are the same as the single-layer neural network but …

… deep learning models for EEG-based BCI applications. Therefore, we introduce this study to
the recent proposed deep learning-… as merits, drawbacks, and applications are introduced. …

… keywords related to HCI and deep learning, such as “… application status of intelligent HCI
in deep learning in various industries is studied, such as gesture recognition, speech interaction…

… In this paper, a brain-computer interface (BCI) system for character recognition is proposed
… This work also proposes a fusion of deep-features with the temporal features for P300 …

… Deep learning networks uses end to end learning process to overcome the … deep learning,
the greater the dataset the performance is good. To improve the performance of deep learning…

… Finally, we extend the application of deep learning to transfer learning in brain-computer
interfaces by training a convolutional auto-encoder on multiple subjects. The subject-…

… into the appropriate BCI applications more effectively using the deep learning technique.
Accordingly, … the contribution of deep learning methods in SSVEP-based BCI applications [6]. …

… Deep learning might serve as one of the translation algorithms … insight into the various deep
learning algorithms that have … Deep Learning algorithms are advanced machine learning …