3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 3 cited
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches
Derick Nganyu Tanyu, Jianfeng Ning, Andreas Hauptmann +2
Electrical Impedance Tomography (EIT) is a powerful imaging technique with diverse applications, e.g., medical diagnosis, industrial monitoring, and environmental studies. The EIT…
eess.IV2023★ 1 cited
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction
Marco Nittscher, Michael Lameter, Riccardo Barbano +3
The deep image prior (DIP) is a well-established unsupervised deep learning method for image reconstruction; yet it is far from being flawless. The DIP overfits to noise if not ear…
math.NA2021
Regularized Orthogonal Nonnegative Matrix Factorization and -means Clustering
Pascal Fernsel, Peter Maass
In this work, we focus on connections between -means clustering approaches and Orthogonal Nonnegative Matrix Factorization (ONMF) methods. We present a novel framework to extrac…