image: Conventional visible spectrum photographs are composed of red, green and blue channels in the visible spectrum. The authors used infrared images of 3 different wavelengths and deep learning to predict the visible spectrum image. view more
Credit: Browne Lab, UC Irvine Department of Ophthalmology, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
Machine learning technology might help humans to see in the dark, with full-color night vision, in proof-of-concept study
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Article URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265185
Article Title: Deep learning to enable color vision in the dark
Author Countries: U.S.A.
Funding: RPB unrestricted grant to UCI Department of Ophthalmology. ICTS KL2 Grant number is KL2 TR001416. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Journal
PLoS ONE
Article Title
Deep learning to enable color vision in the dark
Article Publication Date
6-Apr-2022
COI Statement
The authors have declared that no competing interest exist.