YanhaoHuang23/FAT
FAT:A novel Fourier Adjacency Transformer for advanced EEG emotion recognition (MICCAI 2025))
This project offers an advanced method to automatically classify human emotions by analyzing electroencephalogram (EEG) signals. It takes raw or preprocessed EEG data as input and outputs precise classifications of emotional states (e.g., positive, neutral, negative, joy, anger). Researchers and practitioners in neuroscience, psychology, and human-computer interaction who work with brainwave data will find this useful.
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Use this if you need highly accurate, automated emotion classification from EEG recordings, especially when dealing with noisy or complex brain activity data.
Not ideal if you are looking for a simple, off-the-shelf application for non-EEG emotion recognition (e.g., from facial expressions or text) or a solution that doesn't require technical expertise to implement.
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34
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2
Language
Python
License
MIT
Category
Last pushed
Oct 09, 2025
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