17 citations · 34 across the 5 of their papers we have counts for
6 papers
Uncertainty Tube Visualization of Particle Trajectories
Jixian Li, Timbwaoga Aime Judicael Ouermi, Mengjiao Han +1
Predicting particle trajectories with neural networks (NNs) has substantially enhanced many scientific and engineering domains. However, effectively quantifying and visualizing the…
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks
Mengjiao Han, Jixian Li, Sudhanshu Sane +4
In this paper, we present a comprehensive evaluation to establish a robust and efficient framework for Lagrangian-based particle tracing using deep neural networks (DNNs). Han et a…
Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles
Mengjiao Han, Tushar M. Athawale, David Pugmire +1
Visualizing the uncertainty of ensemble simulations is challenging due to the large size and multivariate and temporal features of ensemble data sets. One popular approach to study…
Exploratory Lagrangian-Based Particle Tracing Using Deep Learning
Mengjiao Han, Sudhanshu Sane, Chris R. Johnson
Time-varying vector fields produced by computational fluid dynamics simulations are often prohibitively large and pose challenges for accurate interactive analysis and exploration.…
A Virtual Frame Buffer Abstraction for Parallel Rendering of Large Tiled Display Walls
Mengjiao Han, Ingo Wald, Will Usher +4
We present dw2, a flexible and easy-to-use software infrastructure for interactive rendering of large tiled display walls. Our library represents the tiled display wall as a single…
A Comparison of Rendering Techniques for Large 3D Line Sets with Transparency
Michael Kern, Christoph Neuhauser, Torben Maack +3
This paper presents a comprehensive study of interactive rendering techniques for large 3D line sets with transparency. The rendering of transparent lines is widely used for visual…