FAT
importedsoftware/fat
FAT:A novel Fourier Adjacency Transformer for advanced EEG emotion recognition (MICCAI 2025))
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/YanhaoHuang23/FAT
- Documentation
- unknown
- Tags
- attention · deep-learning · eeg · eeg-transformer · fat · fourier · transformer
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- EEG-Conformerattention · eeg · eeg-transformer · transformer
[TNSRE 23] EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.
- EEG-Transformerattention · eeg · transformer
i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension…
- Medical-Transformerattention · transformer
Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" - MICCAI 2021
A free, simple, recipe nutrition calculator made with Javascript!
- AttnSleepattention · eeg
[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
- EEG-ATCNetattention · eeg
Attention temporal convolutional network for EEG-based motor imagery classification
- api.github.com/repos/YanhaoHuang23/FATretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-10-09, 36 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/20.json→ .entries["fat"]
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