tinysleepnet
importedsoftware/tinysleepnet
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG by Akara Supratak and Yike Guo from The Faculty of ICT, Mahidol University and Imperial College…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- Apache-2.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/akaraspt/tinysleepnet
- Documentation
- unknown
- Tags
- biosignals · cnn · deep-learning · eeg · neural-networks · rnn · sleep-analysis · sleep-stage-scoring
- 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.
- AttnSleepeeg · sleep-stage-scoring
[TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"
- NeuroNeteeg · sleep-stage-scoring
[Arxiv] NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG
- deepsleepnetbiosignals · cnn · eeg
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
Official source code of Arrhythmia Detection
In this project, we wish to identify psychiatric disorders through patient's speech
- elata-bio-sdkbiosignals · eeg
Elata SDK is the cross-platform biosignal toolkit for building neurotechnology and remote biosensing apps on web and native.
- api.github.com/repos/akaraspt/tinysleepnetretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-08-23, 177 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/49.json→ .entries["tinysleepnet"]
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