DHS Center of Excellence - CAOE

Fingerprint The fingerprint is based on mining the text of the scientific documents related to the associated persons. Based on that an index of weighted terms is created, which defines the key subjects of research unit

Visualization Engineering & Materials Science
Trajectories Engineering & Materials Science
Visual Analytics Mathematics
Semantics Engineering & Materials Science
Cosmology Engineering & Materials Science
Data flow analysis Engineering & Materials Science
Geographical distribution Engineering & Materials Science
Data mining Engineering & Materials Science

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Research Output 2016 2019

  • 23 Article
  • 5 Conference contribution
  • 1 Editorial
  • 1 Review article

Exploring the Sensitivity of Choropleths under Attribute Uncertainty

Huang, Z., Lu, Y., Mack, E., Chen, W. & Maciejewski, R., Jan 1 2019, (Accepted/In press) In : IEEE Transactions on Visualization and Computer Graphics.

Research output: Contribution to journalArticle

Visualization
Data visualization
Autocorrelation
Uncertainty
Statistical methods

Hierarchical Image Semantics using Probabilistic Path Propagations for Biomedical Research

Gillmann, C., Post, T., Wischgoll, T., Hagen, H. & Maciejewski, R., Jan 1 2019, (Accepted/In press) In : IEEE Computer Graphics and Applications.

Research output: Contribution to journalArticle

Image segmentation
Semantics
Electric fuses
Tumors
Communication
1 Citations

Urban form and composition of street canyons: A human-centric big data and deep learning approach

Middel, A., Lukasczyk, J., Zakrzewski, S., Arnold, M. & Maciejewski, R., Mar 1 2019, In : Landscape and Urban Planning. 183, p. 122-132 11 p.

Research output: Contribution to journalArticle

street canyon
learning
pedestrian
field of view
void