openmedical/registry
← registry

ADAST

imported

software/adast

[IEEE TETCI] "ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training"

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

ADAST project image
GitHub preview card for emadeldeen24/ADAST. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
attention-mechanism · deep-learning · domain-adaptation · eeg · pseudo-label · self-attention · self-training · sleep-stage-classification
Regulatory
unknown
built by · 1

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.

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 · self-attention · sleep-stage-classification

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

  • attention-based-bilstm-sleep-scoringattention-mechanism · sleep-stage-classification

    Codes related to the paper "Attention-Based CNN-BiLSTM for Sleep States Classification of Spatiotemporal Wide-Field Calcium Imaging Data"

  • NeuroNeteeg · sleep-stage-classification

    [Arxiv] NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG

  • deconverself-attention

    Official PyTorch Implementation of "Deconver: A Deconvolutional Network for Medical Image Segmentation"

  • ECGTransFormself-attention

    [Biomedical Signal Processing and Control] ECGTransForm: Empowering adaptive ECG arrhythmia classification framework with bidirectional transformer

  • MVG-CNNsleep-stage-classification

    Codes related to paper "Automated sleep stage classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning"

sources
  1. api.github.com/repos/emadeldeen24/ADAST
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2023-09-06, 38 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 →

machine-readable

/v1/entries/4.json→ .entries["adast"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.