MIT Yes Boston University, City University of Hong Kong, NEEPU NITRC EEG Deep Learning Library Python EEG-DL is a Deep Learning (DL) library written by TensorFlow for EEG Tasks (Signals) Classification. The platform provides access to the most advanced deep learning algorithms, which are regularly updated to ensure their effectiveness. Related Work: 1. A Novel Approach of Decoding EEG Four-class Motor Imagery Tasks via Scout ESI and CNN Link: https://iopscience.iop.org/article/10.1088/1741-2552/ab4af6/meta 2. GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals Link: https://ieeexplore.ieee.org/document/9889159 3. Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition Link: https://www.frontiersin.org/articles/10.3389/fbioe.2021.706229/full 4. Attention-based Graph ResNet for Motor Intent Detection from Raw EEG signals Link: https://arxiv.org/abs/2007.13484 EEG Deep Learning Library EEG/MEG, MIT, Algorithm or Reusable Library, Python http://stage.nitrcce.org/projects/eeg_dl_library/, http://http://www.nitrc.org/projects/eeg_dl_library/