A multi-resolution hybrid deep feature extraction and ensemble learning framework for OCT-based methamphetamine addiction detection.
- DOI
- 10.1016/j.pscychresns.2026.112329
- Published
- 2026 Sep 10
- Container
- Psychiatry research. Neuroimaging
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.pscychresns.2026.112329,
title = {A multi-resolution hybrid deep feature extraction and ensemble learning framework for OCT-based methamphetamine addiction detection.},
author = {Bayrak M and Dal D and Barua PD and Dogan S and Tuncer T and Baygin M},
year = {2026},
journal = {Psychiatry research. Neuroimaging},
doi = {10.1016/j.pscychresns.2026.112329},
url = {https://doi.org/10.1016/j.pscychresns.2026.112329}
}RIS
TY - JOUR TI - A multi-resolution hybrid deep feature extraction and ensemble learning framework for OCT-based methamphetamine addiction detection. AU - Bayrak M AU - Dal D AU - Barua PD AU - Dogan S AU - Tuncer T AU - Baygin M PY - 2026 JO - Psychiatry research. Neuroimaging DO - 10.1016/j.pscychresns.2026.112329 UR - https://doi.org/10.1016/j.pscychresns.2026.112329 ER -
APA
M, B., D, D., PD, B., S, D., T, T., & M, B. (2026). A multi-resolution hybrid deep feature extraction and ensemble learning framework for OCT-based methamphetamine addiction detection.. Psychiatry research. Neuroimaging. https://doi.org/10.1016/j.pscychresns.2026.112329
Source records
- pubmed · retrieved 2026-09-26T04:22:16.723Z