Deep Learning-Based Perceptual Stimulus Encoder for Bionic Vision. (arXiv:2203.05604v1 [cs.CV])

Retinal implants have the potential to treat incurable blindness, yet the
quality of the artificial vision they produce is still rudimentary. An
outstanding challenge is identifying electrode activation patterns that lead to
intelligible visual percepts (phosphenes). Here we propose a PSE based on CNN
that is trained in an end-to-end fashion to predict the electrode activation
patterns required to produce a desired visual percept. We demonstrate the
effectiveness of the encoder on MNIST using a psychophysically validated
phosphene model tailored …

arxiv cv deep learning encoder learning stimulus vision