Convolutional Neural Network and Adversarial Autoencoder in EEG images classification
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arXiv
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866914447950348288 |
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| author | Nasybullin, Albert Kurkin, Semen |
| author_facet | Nasybullin, Albert Kurkin, Semen |
| contents | In this paper, we consider applying computer vision algorithms for the classification problem one faces in neuroscience during EEG data analysis. Our approach is to apply a combination of computer vision and neural network methods to solve human brain activity classification problems during hand movement. We pre-processed raw EEG signals and generated 2D EEG topograms. Later, we developed supervised and semi-supervised neural networks to classify different motor cortex activities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_04313 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Convolutional Neural Network and Adversarial Autoencoder in EEG images classification Nasybullin, Albert Kurkin, Semen Machine Learning 68T07, 92C55 I.2.6; I.4.7; J.3 In this paper, we consider applying computer vision algorithms for the classification problem one faces in neuroscience during EEG data analysis. Our approach is to apply a combination of computer vision and neural network methods to solve human brain activity classification problems during hand movement. We pre-processed raw EEG signals and generated 2D EEG topograms. Later, we developed supervised and semi-supervised neural networks to classify different motor cortex activities. |
| title | Convolutional Neural Network and Adversarial Autoencoder in EEG images classification |
| topic | Machine Learning 68T07, 92C55 I.2.6; I.4.7; J.3 |
| url | https://arxiv.org/abs/2604.04313 |