[HTML][HTML] A survey of visual analytics techniques for machine learning

J Yuan, C Chen, W Yang, M Liu, J Xia, S Liu - Computational Visual Media, 2021 - Springer
Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

[HTML][HTML] Deep learning approaches in flow visualization

C Liu, R Jiang, D Wei, C Yang, Y Li, F Wang… - Advances in …, 2022 - Springer
With the development of deep learning (DL) techniques, many tasks in flow visualization that
used to rely on complex analysis algorithms now can be replaced by DL methods. We …

Deep learning and network analysis: Classifying and visualizing accident narratives in construction

B Zhong, X Pan, PED Love, L Ding, W Fang - Automation in Construction, 2020 - Elsevier
If headway is to be made to improve safety performance in construction, then there is a need
to learn from past accidents. Accident reports provide a useful source of information to make …

FlowNet: A deep learning framework for clustering and selection of streamlines and stream surfaces

J Han, J Tao, C Wang - IEEE transactions on visualization and …, 2018 - ieeexplore.ieee.org
For effective flow visualization, identifying representative flow lines or surfaces is an
important problem which has been studied. However, no work can solve the problem for …

Human error analysis for hydraulic engineering: Comprehensive system to reveal accident evolution process with text knowledge

D Tian, H Liu, S Chen, M Li, C Liu - Journal of construction …, 2022 - ascelibrary.org
Many human errors occur in hydraulic engineering construction, and these errors may lead
to huge financial losses. A systematic and comprehensive accident analysis is required to …

A survey of designs for combined 2D+ 3D visual representations

J Hong, R Hnatyshyn, EAD Santos… - … on Visualization and …, 2024 - ieeexplore.ieee.org
We examine visual representations of data that make use of combinations of both 2D and
3D data mappings. Combining 2D and 3D representations is a common technique that …

Multivariate spatial data visualization: a survey

X He, Y Tao, Q Wang, H Lin - Journal of visualization, 2019 - Springer
Multivariate spatial data play an important role in computational science and engineering
simulations. The potential features and hidden relationships in multivariate data can assist …

Visual abstraction and exploration of large-scale geographical social media data

Z Zhou, X Zhang, Z Guo, Y Liu - Neurocomputing, 2020 - Elsevier
A great deal of text and geographical information is provided in the geo-tagged social media
data, which offers unprecedented opportunities to get insights into the social behaviors …

Visual analysis of traffic data based on topic modeling (ChinaVis 2017)

Y Tang, F Sheng, H Zhang, C Shi, X Qin, J Fan - Journal of Visualization, 2018 - Springer
The spatio-temporal urban movement patterns can be extracted from the massive trajectory
data recorded by GPS devices. Effectively analyzing the massive and complex traffic data …

Deep Learning and Network Analysis: Classifying and Visualizing Geologic Hazard Reports

W Li, L Wu, X Xu, Z Xie, Q Qiu, H Liu, Z Huang… - Journal of Earth …, 2024 - Springer
If progress is to be made toward improving geohazard management and emergency
decision-making, then lessons need to be learned from past geohazard information. A …