Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: A review of adaptive feature extraction and classification methods for EEG-based brain-computer interfaces
Semi-supervised feature extraction for EEG classification
Artifact detection in EEG using machine learning
EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks
Deep Feature Learning for EEG Recordings
Active Data Selection for Motor Imagery EEG Classification
Compact Convolutional Neural Networks for Multi-Class, Personalised, Closed-Loop EEG-BCI
Automated Classification of L/R Hand Movement EEG Signals using Advanced Feature Extraction and Machine Learning
Evolving Signal Processing for Brain–Computer Interfaces
Enhanced Low-Latency Detection of Motor Intention From EEG for Closed-Loop Brain-Computer Interface Applications
PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction
Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces
Developing a 3- to 6-state EEG-based brain-computer interface for a robotic manipulator control
Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters
Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients
Emotion recognition from EEG signals by using multivariate empirical mode decomposition
Feature Extraction of EEG Signal using Wavelet Transform
Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination
A novel deep learning approach for classification of EEG motor imagery signals.
A subject transfer framework for EEG classification
EEG signal classification using wavelet feature extraction and a mixture of expert model
Loss of B Cells in Patients with Heterozygous Mutations in IKAROS.
Interplay of metal ions and urease
A survey of content-based image retrieval with high-level semantics
Deep Learning Based Chatbot Models
Adaptive Classification for Brain Computer Interfaces