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Personalized Neural Decoding: User-Adaptive Deep Learning for EEG-Based Image Classification

by Roghayeh Rezaei and Mohammad Almasi

Posted: September 29, 2026
Server: Preprints.org
DOI: 10.20944/preprints202609.2521.v1

This paper focuses on analyzing electroencephalogram (EEG) signals generated by the brain when visualizing images. The study enhances prior research by customizing classifier parameters for each individual user. Initially, a deep learning framework was developed to extract meaningful patterns from raw EEG data and predict images among forty distinct categories from the ImageNet dataset. The central purpose is to adapt this model for new users, enabling the creation of personalized models with minimal additional data.

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