AIMC Topic: Phosphenes
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Machine Learning Techniques for Simulating Human Psychophysical Testing of Low-Resolution Phosphene Face Images in Artificial Vision.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 22, 2025
To evaluate the quality of artificial visual percepts generated by emerging methodologies, researchers often rely on labor-intensive and tedious human psychophysical experiments. These experiments necessitate repeated iterations upon any major/minor ...
Semantic and structural image segmentation for prosthetic vision.
PloS one
Jan 29, 2020
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...
Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.
Brain stimulation
Jul 4, 2019
BACKGROUND: Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation.
Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision.
Artificial intelligence in medicine
Nov 10, 2017
BACKGROUND AND OBJECTIVE: Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual...
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