6 citations · 7 across the 4 of their papers we have counts for
6 papers
Training-Free Stimulus Encoding for Retinal Implants via Sparse Projected Gradient Descent
Henning Konermann, Yuli Wu, Emil Mededovic +3
Retinal implants aim to restore functional vision despite photoreceptor degeneration, yet are fundamentally constrained by low resolution electrode arrays and patient-specific perc…
Evaluating Cross-Subject and Cross-Device Consistency in Visual Fixation Prediction
Yuli Wu, Henning Konermann, Emil Mededovic +2
Understanding cross-subject and cross-device consistency in visual fixation prediction is essential for advancing eye-tracking applications, including visual attention modeling and…
A Pragmatic Note on Evaluating Generative Models with Fréchet Inception Distance for Retinal Image Synthesis
Yuli Wu, Fucheng Liu, Rüveyda Yilmaz +3
Fréchet Inception Distance (FID), computed with an ImageNet pretrained Inception-v3 network, is widely used as a state-of-the-art evaluation metric for generative models. It assume…
Visual Fixation-Based Retinal Prosthetic Simulation
Yuli Wu, Do Dinh Tan Nguyen, Henning Konermann +3
This study proposes a retinal prosthetic simulation framework driven by visual fixations, inspired by the saccade mechanism, and assesses performance improvements through end-to-en…
Optimizing Retinal Prosthetic Stimuli with Conditional Invertible Neural Networks
Yuli Wu, Julian Wittmann, Peter Walter +1
Implantable retinal prostheses offer a promising solution to restore partial vision by circumventing damaged photoreceptor cells in the retina and directly stimulating the remainin…
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
Yuli Wu, Weidong He, Dennis Eschweiler +5
Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data. To overcome this issue, deep generative models can be employed to syn…