EEGNet
importedsoftware/eegnet
This project focuses on implementing CNN model based on the EEGNet architecture with Pytorch library for classifying motor imagery tasks using EEG data.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/amrzhd/EEGNet
- Documentation
- unknown
- Tags
- bci · bci-systems · convolutional-neural-networks · deep-learning · depthwise-convolutions · depthwise-separable-convolutions · eeg · eeg-signals
- 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-Brain-Computer-Interface-to-play-Pongbci · bci-systems · eeg
Developed an Electroencephalography(EEG) based Brain Computer Interface to play Pong with brain activity
- eeg_mi_dlbci · bci-systems · eeg
A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning…
- PyNoetic-officialbci-systems · eeg-signals
PyNoetic: A Modular Python Framework for No-Code Development of EEG Brain-Computer Interfaces
- AugmentedBCIFrameworkbci · eeg · eeg-signals
The UniPA BCI Framework is an Augmented Brain-Computer Interface framework based on the P300 paradigm with further additional modules to perform the acquisition of eye gaze and physiological features.
- LFPDeepStatesbci · bci-systems
neural models for anesthesia stage transition classification
- NeuralFlightbci · eeg-signals
Neural control framework for drones using motor imagery EEG classification. Achieves 73% cross-subject accuracy with PyTorch and enables hands-free drone control through imagined hand/feet movements.
- api.github.com/repos/amrzhd/EEGNetretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-09-08, 172 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/19.json→ .entries["eegnet"]
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