36 citations · 68 across the 11 of their papers we have counts for
11 papers
Accelerating Computation of Stable Merge Tree Edit Distances using Parameterized Heuristics
Florian Wetzels, Heike Leitte, Christoph Garth
In this paper, we present a novel heuristic algorithm for the stable but NP-complete deformation-based edit distance on merge trees. Our key contribution is the introduction of a u…
Branch Decomposition-Independent Edit Distances for Merge Trees
Florian Wetzels, Heike Leitte, Christoph Garth
Edit distances between merge trees of scalar fields have many applications in scientific visualization, such as ensemble analysis, feature tracking or symmetry detection. In this p…
Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional Data
Jan-Tobias Sohns, Michaela Schmitt, Fabian Jirasek +2
Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information. Their explanation, in particular with respect to th…
Knowledge Rocks:Adding Knowledge Assistance to Visualization Systems
Anna-Pia Lohfink, Simon D. Duque Anton, Heike Leitte +1
We present Knowledge Rocks, an implementation strategy and guideline for augmenting visualization systems to knowledge-assisted visualization systems, as defined by the KAVA model.…
Visual Probing and Correction of Object Recognition Models with Interactive user feedback
Viny Saajan Victor, Pramod Vadiraja, Jan-Tobias Sohns +1
With the advent of state-of-the-art machine learning and deep learning technologies, several industries are moving towards the field. Applications of such technologies are highly d…
Security in Process: Visually Supported Triage Analysis in Industrial Process Data
Anna-Pia Lohfink, Simon D. Duque Anton, Hans Dieter Schotten +2
Operation technology networks, i.e. hard- and software used for monitoring and controlling physical/industrial processes, have been considered immune to cyber attacks for a long ti…
Topological Machine Learning with Persistence Indicator Functions
Bastian Rieck, Filip Sadlo, Heike Leitte
Techniques from computational topology, in particular persistent homology, are becoming increasingly relevant for data analysis. Their stable metrics permit the use of many distanc…
Hierarchies and Ranks for Persistence Pairs
Bastian Rieck, Filip Sadlo, Heike Leitte
We develop a novel hierarchy for zero-dimensional persistence pairs, i.e., connected components, which is capable of capturing more fine-grained spatial relations between persisten…
Persistence Concepts for 2D Skeleton Evolution Analysis
Bastian Rieck, Filip Sadlo, Heike Leitte
In this work, we present concepts for the analysis of the evolution of two-dimensional skeletons. By introducing novel persistence concepts, we are able to reduce typical temporal…
Persistent Intersection Homology for the Analysis of Discrete Data
Bastian Rieck, Markus Banagl, Filip Sadlo +1
Topological data analysis is becoming increasingly relevant to support the analysis of unstructured data sets. A common assumption in data analysis is that the data set is a sample…
Feature Extraction from Segmentations of Neuromuscular Junctions
Julia Portl, Heike Leitte
Segmentations are often necessary for the analysis of image data. They are used to identify different objects, for example cell nuclei, mitochondria, or complete cells in microscop…