Abstract
To test tuning methods for the Retina Encoder (RE) of a Retina Implant (RI) as a visual prosthesis for blind subjects with retinal degenerations a suitable simulation of the patient’s evaluative response to RE state alterations must be provided. RE simulates real time retinal information processing and consists of several hundreds of spatio-temporal receptive field (RF) filters to generate electrical signals for ganglion cell (GC) stimulation. We propose a neural network to reconstruct the RE input from a number of consecutive RE output frames. The network can be interpreted as a simulation of a part of the central visual system with GC signals as input and perception visualization as output. We present first results using Evolution Strategies for neural network weight optimization.
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References
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© 1998 Springer-Verlag London
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Becker, M., Braun, M., Eckmiller, R. (1998). Retina Encoder Inversion for Retina Implant Simulation. In: Niklasson, L., Bodén, M., Ziemke, T. (eds) ICANN 98. ICANN 1998. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1599-1_122
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DOI: https://doi.org/10.1007/978-1-4471-1599-1_122
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