Eurographics Partner Events: Recent submissions

Now showing items 641-660 of 2371

    • SepEx: Visual Analysis of Class Separation Measures 

      Bernard, Jürgen; Hutter, Marco; Zeppelzauer, Matthias; Sedlmair, Michael; Munzner, Tamara (The Eurographics Association, 2020)
      Class separation is an important concept in machine learning and visual analytics. However, the comparison of class separation for datasets with varying dimensionality is non-trivial, given a) the various possible structural ...

    • EuroVa 2020: Frontmatter 

      Turkay, Cagatay; Vrotsou, Katerina (The Eurographics Association, 2020)

    • Mesoscope: A Web-based Tool for Mesoscale Data Integration and Curation 

      Autin, Ludovic; Maritan, Martina; Barbaro, Brett A.; Gardner, Adam; Olson, Arthur J.; Sanner, Michel; Goodsell, David S. (The Eurographics Association, 2020)
      Interest is growing for 3D models of the biological mesoscale, the intermediate scale between the nanometer scale of molecular structure and micrometer scale of cellular biology. However, it is currently difficult to gather, ...

    • Improved Umbrella Visualization implemented in UnityMol gives valuable insight on sugar/protein interplay 

      Besançon, Camille; Wong, Hua; Rao, Rajas; Dauchez, Manuel; Belloy, Nicolas; Prévoteau-Jonquet, Jessica; Baud, Stéphanie (The Eurographics Association, 2020)
      Among the various post-translational modifications, N-glycosylations are particularly important. They are linked to asparagine residues and their function as well as the one of the protein can be altered by modifications ...

    • The Vesicle Builder - A Membrane Packing Algorithm for the CELLmicrocosmos MembraneEditor 

      Giuliari, Beatrice; Kösters, Manuel; Zhou, Jan; Dingersen, Tim; Heissmann, André; Rotzoll, Ralf; Krüger, Jens; Giorgetti, Alejandro; Sommer, Björn (The Eurographics Association, 2020)
      For a long time, the major focus of membrane simulations was laid on rectangular membrane patches based on the fluid mosaic model. Because of the computational performance of today's computer hardware, it is now possible ...

    • Molecular Binding in a Visuohaptic Environment: An Enhanced Approach in STEM Learning 

      Yasmin, Shamima; Quick, Rhianna (The Eurographics Association, 2020)
      Learning science, technology, engineering, and mathematics (STEM) can be dull in the absence of adequate incentives; students may lose interest in STEM subjects during their high school education. This could result in a ...

    • MolVa 2020: Frontmatter 

      Byška, Jan; Krone, Michael; Sommer, Björn (The Eurographics Association, 2020)

    • Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders 

      Grósz, Tamás; Kurimo, Mikko (The Eurographics Association, 2020)
      In the past few years, Deep Neural Networks (DNN) have become the state-of-the-art solution in several areas, including automatic speech recognition (ASR), unfortunately, they are generally viewed as black boxes. Recently, ...

    • Improving the Sensitivity of Statistical Testing for Clusterability with Mirrored-Density Plots 

      Thrun, Michael C. (The Eurographics Association, 2020)
      For many applications, it is crucial to decide if a dataset possesses cluster structures. This property is called clusterability and is usually investigated with the usage of statistical testing. Here, it is proposed to ...

    • Visual Analysis of the Impact of Neural Network Hyper-Parameters 

      Jönsson, Daniel; Eilertsen, Gabriel; Shi, Hezi; Zheng, Jianmin; Ynnerman, Anders; Unger, Jonas (The Eurographics Association, 2020)
      We present an analysis of the impact of hyper-parameters for an ensemble of neural networks using tailored visualization techniques to understand the complicated relationship between hyper-parameters and model performance. ...

    • 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 ...

    • Progressive Multidimensional Projections: A Process Model based on Vector Quantization 

      Ventocilla, Elio Alejandro; Martins, Rafael M.; Paulovich, Fernando V.; Riveiro, Maria (The Eurographics Association, 2020)
      As large datasets become more common, so becomes the necessity for exploratory approaches that allow iterative, trial-anderror analysis. Without such solutions, hypothesis testing and exploratory data analysis may become ...

    • MLVis 2020: Frontmatter 

      Archambault, Daniel; Nabney, Ian; Peltonen, Jaakko (The Eurographics Association, 2020)

    • 3D Human Body Skeleton Extraction from Consecutive Surfaces 

      Zhang, Yong; Tan, Fei; Wang, Shaofan; Kong, Dehui; Yin, Baocai (The Eurographics Association, 2019)
      Extracting human body skeletons from consecutive surfaces is an important research topic in the fields of computer graphics and human computer interaction, especially in posture estimation and skeleton animation. Current ...

    • Feature Curve Network Extraction via Quadric Surface Fitting 

      Zhengda, Lu; Guo, Jianwei; Xiao, Jun; Wang, Ying; Zhang, Xiaopeng; Yan, Dong-Ming (The Eurographics Association, 2019)
      Feature curves on 3D shapes provide a high dimensional representation of the geometry and reveal their underlying structure. In this paper, we present an automatic approach for extracting complete feature curve networks ...

    • External Forces Guided Fluid Surface and Volume Reconstruction from Monocular Video 

      Nie, Xiaoying; Hu, Yong; Su, Zhiyuan; Shen, Xukun (The Eurographics Association, 2019)
      We propose a novel method to reconstruct fluid's volume movement and surface details from just a monocular video for the first time. Although many monocular video-based reconstruction methods have been developed, the ...

    • LPaintB: Learning to Paint from Self-Supervision 

      Jia, Biao; Brandt, Jonathan; Mech, Radomír; Kim, Byungmoon; Manocha, Dinesh (The Eurographics Association, 2019)
      We present a novel reinforcement learning-based natural media painting algorithm. Our goal is to reproduce a reference image using brush strokes and we encode the objective through observations. Our formulation takes into ...

    • Towards Biomechanically and Visually Plausible Volumetric Cutting Simulation of Deformable Bodies 

      Qian, Yinling; Huang, Wenbin; Si, Weixin; Liao, Xiangyun; Wang, Qiong; Heng, Pheng-Ann (The Eurographics Association, 2019)
      Due to the simplicity and high efficiency, composited finite element method(CFEM) based virtual cutting attracted much attention in the field of virtual surgery in recent years. Even great progress has been made in volumetric ...

    • Gaze Attention and Flow Visualization using the Smudge Effect 

      Yoo, Sangbong; Jeong, Seongmin; Kim, Seokyeon; Jang, Yun (The Eurographics Association, 2019)
      Many advanced gaze visualization techniques have been developed continuously based on the fundamental gaze visualizations such as scatter plots, attention map, and scanpath. However, it is not easy to locate challenging ...

    • Connectivity-preserving Smooth Surface Filling with Sharp Features 

      Lescoat, Thibault; Memari, Pooran; Thiery, Jean-Marc; Ovsjanikov, Maks; Boubekeur, Tamy (The Eurographics Association, 2019)
      We present a method for constructing a surface mesh filling gaps between the boundaries of multiple disconnected input components. Unlike previous works, our method pays special attention to preserving both the connectivity ...