Now showing items 1-3 of 3

    • ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods 

      Schlegel, Udo; Cakmak, Eren; Keim, Daniel A. (The Eurographics Association, 2020)
      Explainable artificial intelligence (XAI) methods aim to reveal the non-transparent decision-making mechanisms of black-box models. The evaluation of insight generated by such XAI methods remains challenging as the applied ...
    • MotionGlyphs: Visual Abstraction of Spatio-Temporal Networks in Collective Animal Behavior 

      Cakmak, Eren; Schäfer, Hanna; Buchmüller, Juri; Fuchs, Johannes; Schreck, Tobias; Jordan, Alex; Keim, Daniel A. (The Eurographics Association and John Wiley & Sons Ltd., 2020)
      Domain experts for collective animal behavior analyze relationships between single animal movers and groups of animals over time and space to detect emergent group properties. A common way to interpret this type of data ...
    • SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations 

      Buchmüller, Juri F.; Schlegel, Udo; Cakmak, Eren; Keim, Daniel A.; Dimara, Evanthia (The Eurographics Association, 2020)
      Compact visual summaries of spatio-temporal movement data often strive to express accurate positions of movers. We present SpatialRugs, a technique to enhance the spatial awareness of movements in dense pixel visualizations. ...