Skip to content
DraconiticResearch
Search Sources API
203,952 studies31 sourcesUpdated 10 min ago
Peer-reviewedCC BYBioengineering (Basel, Switzerland)

HM-Swin: Hierarchical Multiscale Swin Transformer Network with Attention Fusion for Heart Sound Classification

Related

  1. HierTAC-Net: a robust and explainable hierarchical attention network for multi-configuration gastrointestinal endoscopic image classification
    Md. Masum Mia, Amith Khandakar, Sawal Hamid Md Ali +3
    Scientific ReportsPeer-reviewedCC BY 4.0Full textOncologyCrossref
  2. Multiscale POD of Transformer Attention Fields: Scale-Selective Analysis via Morlet Scalogram
    Athanasios Zeris
    arXivPreprintCC BY 4.0Full textFluid dynamicsarXiv
  3. MangoSwin-attention: a swin transformer with attention pooling for generalizable mango leaf disease classification
    Saksham Khurana, Valarmathi Prahasam, Brindha Subburaj +2
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textPlant biologyCrossref
  4. An attention-based CNN–Transformer hybrid framework for osteoporosis and osteopenia classification in knee X-ray images
    Puneet Kumar, Deepika Kumar, Abhishek Kumar +1
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textCrossref
  5. Attention-integrated hybrid CNN–vision transformer framework for robust multi-class cervical cytology classification using liquid-based cytology images
    A. Sathiya, R. Madonna Arieth, C. M. Nalayini +1
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textCrossref
BibTeX
@article{anon2026hmswin,
  title = {{HM-Swin: Hierarchical Multiscale Swin Transformer Network with Attention Fusion for Heart Sound Classification}},
  journal = {Bioengineering (Basel, Switzerland)},
  year = {2026},
  month = oct,
  url = {https://europepmc.org/article/PMC/PMC13701524},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - HM-Swin: Hierarchical Multiscale Swin Transformer Network with Attention Fusion for Heart Sound Classification
PY  - 2026
DA  - 2026/10/01
JO  - Bioengineering (Basel, Switzerland)
UR  - https://europepmc.org/article/PMC/PMC13701524
SN  - 2306-5354
ER  -