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Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals

In this repository, we provide the code and the datasets that we use to conduct this research topic.

Xiang Zhang, Xiaocong Chen, Manqing Dong, Huan Liu, Chang Ge, and Lina Yao. Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals. The 26th International Conference On Neural Information Processing (ICONIP 2019). Sydney, Australia, December 12-15, 2019. Retrieved from: https://arxiv.org/abs/1907.13351

EEG feature learning

In EEG_featurelearning.py, we put our CNN classifier which used to extract EEG features.

Multi-task GAN

In GAN_shape.py, we build a multi-task GAN along with the semantic alignment to reconstruct the shapes.

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Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain Signals, published in ICONIP 2019.

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