Eeg-Based Video Identification Using Graph Signal Modeling and Graph Convolutional Neural Network

Soobeom Jang; Seong-Eun Moon; Jong-Seok Lee

ICASSP 2018accepted0 citations

Eeg-Based Video Identification Using Graph Signal Modeling and Graph Convolutional Neural Network

Soobeom Jang, Seong-Eun Moon, Jong-Seok Lee

Abstract

This paper proposes a novel graph signal-based deep learning method for electroencephalography (EEG) and its application to EEG-based video identification. We present new methods to effectively represent EEG data as signals on graphs, and learn them using graph convolutional neural networks. Experimental results for video identification using EEG responses obtained while watching videos show the effectiveness of the proposed approach in comparison to existing methods. Effective schemes for graph signal representation of EEG are also discussed.

BibTeX

@inproceedings{icassp2018_eegbasedvideoide,
  title = {Eeg-Based Video Identification Using Graph Signal Modeling and Graph Convolutional Neural Network},
  author = {Soobeom Jang and Seong-Eun Moon and Jong-Seok Lee},
  booktitle = {ICASSP 2018},
  year = {2018}
}