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EEG

Electroencephalography epilepsy

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Showing 1601–1625 of 2431 papers

TitleStatusHype
Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection—0
Real-Time Emotion Classification Using EEG Data Stream in E-Learning ContextsCode1
A New Neuromorphic Computing Approach for Epileptic Seizure Prediction—0
Dynamic Graph Modeling of Simultaneous EEG and Eye-tracking Data for Reading Task Identification—0
Characterising Alzheimer's Disease with EEG-based Energy Landscape AnalysisCode0
Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization—0
Analysis of EEG data using complex geometric structurization—0
Decoding EEG Brain Activity for Multi-Modal Natural Language Processing—0
EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks—0
Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder—0
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
Classification of multivariate weakly-labelled time-series with attentionCode0
Geometric feature performance under downsampling for EEG classification tasks—0
EEGs disclose significant brain activity correlated with synaptic fickleness—0
Mind the beat: detecting audio onsets from EEG recordings of music listening—0
HNPE: Leveraging Global Parameters for Neural Posterior EstimationCode1
End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax—0
Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning—0
A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure predictionCode0
RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020Code0
Extracting the Auditory Attention in a Dual-Speaker Scenario from EEG using a Joint CNN-LSTM ModelCode1
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
ScalingNet: extracting features from raw EEG data for emotion recognition—0
EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognition—0
MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG ClassificationCode1
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