activity
20192021
most citedRevisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study

84 citations · 86 across the 3 of their papers we have counts for

collaborators

5 papers

cs.HC202184 cited

Revisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study

Jiazhi Xia, Yuchen Zhang, Jie Song +3

Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual exploration of cluster structures of high-dimensional datasets. However, different DR techniq…

cs.DS2021

SpEuler: Semantics-preserving Euler Diagrams

Rebecca Kehlbeck, Jochen Görtler, Yunhai Wang +1

Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverag…

cs.CV2021

Scribble-Supervised Semantic Segmentation by Uncertainty Reduction on Neural Representation and Self-Supervision on Neural Eigenspace

Zhiyi Pan, Peng Jiang, Yunhai Wang +2

Scribble-supervised semantic segmentation has gained much attention recently for its promising performance without high-quality annotations. Due to the lack of supervision, confide…

cs.GR20202 cited

Palettailor: Discriminable Colorization for Categorical Data

Kecheng Lu, Mi Feng, Xin Chen +5

We present an integrated approach for creating and assigning color palettes to different visualizations such as multi-class scatterplots, line, and bar charts. While other methods…

cs.CV2019

Deep-Learning Inversion of Seismic Data

Shucai Li, Bin Liu, Yuxiao Ren +4

We propose a new method to tackle the mapping challenge from time-series data to spatial image in the field of seismic exploration, i.e., reconstructing the velocity model directly…