Diagnostic features predicted by deep learning improve human object recognition in simulated prosthetic vision
- DOI
- 10.1088/1741-2552/ae9227
- Published
- 2026-08-01
- Container
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1088/1741-2552/ae9227,
title = {Diagnostic features predicted by deep learning improve human object recognition in simulated prosthetic vision},
author = {Elsa Scialom and Ben Lonnqvist and Alban Bornet and Michael H Herzog},
year = {2026},
journal = {Journal of Neural Engineering},
doi = {10.1088/1741-2552/ae9227},
url = {https://doi.org/10.1088/1741-2552/ae9227}
}RIS
TY - JOUR TI - Diagnostic features predicted by deep learning improve human object recognition in simulated prosthetic vision AU - Elsa Scialom AU - Ben Lonnqvist AU - Alban Bornet AU - Michael H Herzog PY - 2026 JO - Journal of Neural Engineering DO - 10.1088/1741-2552/ae9227 UR - https://doi.org/10.1088/1741-2552/ae9227 ER -
APA
Scialom, E., Lonnqvist, B., Bornet, A., & Herzog, M. H. (2026). Diagnostic features predicted by deep learning improve human object recognition in simulated prosthetic vision. Journal of Neural Engineering. https://doi.org/10.1088/1741-2552/ae9227
Source records
- crossref · retrieved 2026-09-25T15:00:03.222Z