PhD thesis defense to be held on May 29, 2023, at 10:00 (Teleteaching Room, NTUA Central Library)

Picture Credit: Nikos Melanitis-Paraskevas

Thesis title: Biologically-inspired computer vision methods in retinal prosthesis

Abstract: In this thesis, we introduce Retina Ganglion Cell (RGC) models that integrate the current understanding of RGC functions in a preprocessing feature extraction step. Towards the perspective of improved Retinal Prosthesis interventions, we propose a Computer Vision (CV) image preprocessing method based on RGCs functions and then use the method to reproduce retina output with a standard Generalized Integrate & Fire (GIF) neuron model. To put further focus on retina models we trained Linear-Nonlinear (LN) models using response data from biological retinae. Finally, we explore visual attention, with a focus on improving prosthetic vision, including retinal as well as cortical implants in our analysis. Our results show that in primary visual cortex (V1), a subset of around 10% of the neurons responds differently to salient versus non-salient visual regions. Visual attention information was not traced in retinal response. It appears that the retina remains naive concerning visual attention; cortical response gets modulated to interpret visual attention information.

Supervisor: Professor Konstantina Nikita

PhD Student: Nikos Melanitis-Paraskevas