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CareSleepNet

imported

software/caresleepnet

[JBHI 2024] CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging

Machine-generated from the listed sources and not yet reviewed by a human.

CareSleepNet project image
GitHub preview card for wjq-learning/CareSleepNet. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
convolutional-neural-networks · deep-learning · eeg · sleep-staging · transformer
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • AttnSleepeeg · sleep-staging

    [TNSRE 2021] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"

  • CountingSheepPSGeeg · sleep-staging

    EEGLAB-compatible analysis software for manual / visual sleep stage scoring, signal processing and event marking of polysomnographic (PSG) data for MATLAB.

  • SleepDGeeg · sleep-staging

    [AAAI 2024] Generalizable Sleep Staging via Multi-Level Domain Alignment

  • sleepecgsleep-staging

    Sleep stage detection using ECG

  • pdf-brainconvolutional-neural-networks · transformer

    📚 Index and enrich your PDFs and Markdown files locally for a powerful, unified knowledge base with semantic search capabilities.

  • EEG-Conformereeg · transformer

    [TNSRE 23] EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

sources
  1. api.github.com/repos/wjq-learning/CareSleepNet
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2025-06-06, 19 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 →

machine-readable

/v1/entries/34.json→ .entries["caresleepnet"]

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