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Peer-reviewedLicence not statedThe Journal of Supercomputing

ArrhythmiaVision: resource-conscious deep learning models with visual explanations for ECG arrhythmia classification

  • Z. Tanveer Baig1
  • Sidra Nasir2
  • Rizwan Ahmed Khan3
  • Muhammad Zeeshan Ul Haque4
4 affiliations
  1. 1Department of Electrical Engineering and Information Technology, Otto von Guerricke Universität, Magdeburg, Germany
  2. 2Dipartimento di Informatica, Universitá di Verona, Verona, Italy
  3. 3Department of Computer Science, School of Mathematics and Computer Science, Institute of Business Administration, Karachi, Pakistan
  4. 4Department of Biomedical Engineering, Salim Habib University, Karachi, Pakistan
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Cite

BibTeXRIS
BibTeX
@article{baig2026arrhythmiavision,
  title = {{ArrhythmiaVision: resource-conscious deep learning models with visual explanations for ECG arrhythmia classification}},
  author = {Z. Tanveer Baig and Sidra Nasir and Rizwan Ahmed Khan and Muhammad Zeeshan Ul Haque},
  journal = {The Journal of Supercomputing},
  year = {2026},
  month = jun,
  doi = {10.1007/s11227-026-08629-9},
  url = {http://arxiv.org/abs/2505.03787},
}
RIS
TY  - JOUR
TI  - ArrhythmiaVision: resource-conscious deep learning models with visual explanations for ECG arrhythmia classification
AU  - Z. Tanveer Baig
AU  - Sidra Nasir
AU  - Rizwan Ahmed Khan
AU  - Muhammad Zeeshan Ul Haque
PY  - 2026
DA  - 2026/06/03
JO  - The Journal of Supercomputing
DO  - 10.1007/s11227-026-08629-9
UR  - http://arxiv.org/abs/2505.03787
SN  - 0920-8542
SN  - 1573-0484
ER  -