7 citations · 19 across the 7 of their papers we have counts for
14 papers
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images
Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit +7
Quantifying the perceptual similarity of two images is a long-standing problem in low-level computer vision. The natural image domain commonly relies on supervised learning, e.g.,…
Topologically faithful image segmentation via induced matching of persistence barcodes
Nico Stucki, Johannes C. Paetzold, Suprosanna Shit +2
Image segmentation is a largely researched field where neural networks find vast applications in many facets of technology. Some of the most popular approaches to train segmentatio…
Relationformer: A Unified Framework for Image-to-Graph Generation
Suprosanna Shit, Rajat Koner, Bastian Wittmann +8
A comprehensive representation of an image requires understanding objects and their mutual relationship, especially in image-to-graph generation, e.g., road network extraction, blo…
SoK: Differential Privacy on Graph-Structured Data
Tamara T. Mueller, Dmitrii Usynin, Johannes C. Paetzold +2
In this work, we study the applications of differential privacy (DP) in the context of graph-structured data. We discuss the formulations of DP applicable to the publication of gra…
A Deep Learning Approach to Predicting Collateral Flow in Stroke Patients Using Radiomic Features from Perfusion Images
Giles Tetteh, Fernando Navarro, Johannes Paetzold +3
Collateral circulation results from specialized anastomotic channels which are capable of providing oxygenated blood to regions with compromised blood flow caused by ischemic injur…
Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
Suprosanna Shit, Ivan Ezhov, Leon Mächler +6
Fast and accurate solutions of time-dependent partial differential equations (PDEs) are of pivotal interest to many research fields, including physics, engineering, and biology. Ge…