BWGAN-GP: An EEG Data Generation Method for Class Imbalance Problem in RSVP Tasks

BWGAN-GP: An EEG Data Generation Method for Class Imbalance Problem in RSVP Tasks

In the rapid serial visual presentation (RSVP) classification task, the data from the target and non-target classes are incredibly imbalanced. These class imbalance problems (CIPs) can hinder the classifier from achieving better performance, especially in deep learning. This paper proposed a novel d...

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Bibliographic Details
Main Authors: Meng Xu, Yuanfang Chen, Yijun Wang, Dan Wang, Zehua Liu, Lijian Zhang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Rapid serial visual presentation (RSVP)
Wasserstein generative adversarial network (WGAN)
data augmentation
class imbalance problem
auto-encoder
Online Access:https://ieeexplore.ieee.org/document/9690467/

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