3 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.IV2024★ 3 cited
Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan
Super-resolution (SR) is an ill-posed inverse problem, where the size of the set of feasible solutions that are consistent with a given low-resolution image is very large. Many alg…
eess.IV2024
Trustworthy SR: Resolving Ambiguity in Image Super-resolution via Diffusion Models and Human Feedback
Cansu Korkmaz, Ege Cirakman, A. Murat Tekalp +1
Super-resolution (SR) is an ill-posed inverse problem with a large set of feasible solutions that are consistent with a given low-resolution image. Various deterministic algorithms…
cs.LG2023
Optimal Nonlinearities Improve Generalization Performance of Random Features
Samet Demir, Zafer Doğan
Random feature model with a nonlinear activation function has been shown to perform asymptotically equivalent to a Gaussian model in terms of training and generalization errors. An…