IntNet: Lightweight yet high-performance deep learning system for intuitive radar patterns analysis and human fall detection
- DOI
- 10.1016/j.compbiomed.2026.111485
- Published
- 2026-02
- Container
- Computers in Biology and Medicine
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.compbiomed.2026.111485,
title = {IntNet: Lightweight yet high-performance deep learning system for intuitive radar patterns analysis and human fall detection},
author = {Malek Y. Almallah and Belal H. Sababha},
year = {2026},
journal = {Computers in Biology and Medicine},
doi = {10.1016/j.compbiomed.2026.111485},
url = {https://doi.org/10.1016/j.compbiomed.2026.111485}
}RIS
TY - JOUR TI - IntNet: Lightweight yet high-performance deep learning system for intuitive radar patterns analysis and human fall detection AU - Malek Y. Almallah AU - Belal H. Sababha PY - 2026 JO - Computers in Biology and Medicine DO - 10.1016/j.compbiomed.2026.111485 UR - https://doi.org/10.1016/j.compbiomed.2026.111485 ER -
APA
Almallah, M. Y., & Sababha, B. H. (2026). IntNet: Lightweight yet high-performance deep learning system for intuitive radar patterns analysis and human fall detection. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2026.111485
Source records
- crossref · retrieved 2026-09-25T17:31:52.897Z