A Robust Multi-Branch CNN-LSTM Architecture for Cross-Subject Motor Imagery Classification.
- DOI
- 10.3390/s26113310
- Published
- 2026 May 23
- Container
- Sensors (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/s26113310,
title = {A Robust Multi-Branch CNN-LSTM Architecture for Cross-Subject Motor Imagery Classification.},
author = {Zini S and Bidone F and Napoletano P},
year = {2026},
journal = {Sensors (Basel, Switzerland)},
doi = {10.3390/s26113310},
url = {https://doi.org/10.3390/s26113310}
}RIS
TY - JOUR TI - A Robust Multi-Branch CNN-LSTM Architecture for Cross-Subject Motor Imagery Classification. AU - Zini S AU - Bidone F AU - Napoletano P PY - 2026 JO - Sensors (Basel, Switzerland) DO - 10.3390/s26113310 UR - https://doi.org/10.3390/s26113310 ER -
APA
S, Z., F, B., & P, N. (2026). A Robust Multi-Branch CNN-LSTM Architecture for Cross-Subject Motor Imagery Classification.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26113310
Source records
- pubmed · retrieved 2026-09-25T09:21:45.335Z