A Wentzel,C Floricel,G Canahuate et al.
A Wentzel et al.
Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent organs at risk. We describe the co-design of a modeling system,...
Smooth Interpolating Curves with Local Control and Monotone Alternating Curvature [0.03%]
具有局部控制和交替单调曲率的光滑插值曲线
Alexandre Binninger,Olga Sorkine-Hornung
Alexandre Binninger
We propose a method for the construction of a planar curve based on piecewise clothoids and straight lines that intuitively interpolates a given sequence of control points. Our method has several desirable properties that are not simultaneo...
Hex Me If You Can [0.03%]
如果你能的话就十六进制我一下
P-A Beaufort,M Reberol,D Kalmykov et al.
P-A Beaufort et al.
HexMe consists of 189 tetrahedral meshes with tagged features and a workflow to generate them. The primary purpose of HexMe meshes is to enable consistent and practically meaningful evaluation of hexahedral meshing algorithms and related te...
Non-Isometric Shape Matching via Functional Maps on Landmark-Adapted Bases [0.03%]
基于标志适应基的功能映射非等距形状匹配
Mikhail Panine,Maxime Kirgo,Maks Ovsjanikov
Mikhail Panine
We propose a principled approach for non-isometric landmark-preserving non-rigid shape matching. Our method is based on the functional map framework, but rather than promoting isometries we focus on near-conformal maps that preserve landmar...
N Piccolotto,M Bögl,C Muehlmann et al.
N Piccolotto et al.
Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measu...
Feng Wang,Nathan Marshak,Will Usher et al.
Feng Wang et al.
Adaptive mesh refinement (AMR) techniques allow for representing a simulation's computation domain in an adaptive fashion. Although these techniques have found widespread adoption in high-performance computing simulations, visualizing their...
Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning [0.03%]
基于无监督深度表征学习的序列表中交互式视觉模式搜索（PEAX）
Fritz Lekschas,Brant Peterson,Daniel Haehn et al.
Fritz Lekschas et al.
We present Peax, a novel feature-based technique for interactive visual pattern search in sequential data, like time series or data mapped to a genome sequence. Visually searching for patterns by similarity is often challenging because of t...
Roger A Leite,Theresia Gschwandtner,Silvia Miksch et al.
Roger A Leite et al.
Trust-ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well-defined problems, analyti...
Davide Ceneda,Natalia Andrienko,Gennady Andrienko et al.
Davide Ceneda et al.
Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches shou...