Scientific Visualization and Computer Graphics

Organisational unit: Research Group

  1. 2017
  2. Valentijn, E. A., Begeman, K., Belikov, A., Boxhoorn, D. R., Brinchmann, J., McFarland, J., ... van Dijk, G. J. W. (2017). Target and (Astro-)WISE technologies - Data federations and its applications. In Astroinformatics 2017 (pp. 333-340). (Proceedings IAU Symposium; Vol. 12, issue S325, Astroinformatics). International Astronomical Union. DOI: 10.1017/S1743921317000254
  3. van der Ree, M., Roerdink, J., Phillips, C., Garraux, G., Salmon, E., & Wiering, M. (2017). Support Vector Components Analysis. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: ESANN
  4. Okafor, E., Pawara, P., Karaaba, M., Surinta, O., Codreanu, V., Schomaker, L., & Wiering, M. (2017). Comparative study between deep learning and bag of visual words for wild-animal recognition. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). Institute of Electrical and Electronics Engineers Inc.. DOI: 10.1109/SSCI.2016.7850111
  5. Hettinga, G., & Kosinka, J. (2017). Phong Tessellation and PN Polygons for Polygonal Models. In Eurographics 2017 - short papers (2 ed., Vol. 36). Eurographics (European Association for Computer Graphics).
  6. 2016
  7. Biehl, M., Mudali, D., Leenders, K. L., & Roerdink, J. B. T. M. (2016). Classification of FDG-PET Brain Data by Generalized Matrix Relevance LVQ. In K. Amunts, L. Grandinetti, T. Lippert, & N. Petkov (Eds.), Brain-Inspired Computing: Second International Workshop, BrainComp 2015, Cetraro, Italy, July 6-10, 2015, Revised Selected Papers (pp. 131-141). (Lecture Notes in Computer Science; Vol. 10087). Cham: Springer International Publishing. DOI: 10.1007/978-3-319-50862-7_10
  8. Mudali, D., Biehl, M., Leenders, K., & Roerdink, J. (2016). LVQ and SVM Classification of FDG-PET Brain Data. In E. Merényi, M. J. Mendenhall, & P. O'Driscoll (Eds.), Advances in Self-Organizing Maps and Learning Vector Quantization (Vol. 428, pp. 205-215). (Advances in Intelligent Systems and Computing). Springer. DOI: 10.1007/978-3-319-28518-4_18
  9. Ahrens, J., Andrienko, G., Chen, M., Lee, B., Ma, K-L., Roerdink, J., ... Qu, H. (2016). Message from the Paper Chairs and Guest Editors. Ieee transactions on visualization and computer graphics, 22(1), xi-xv.
  10. Ponjou Tasse, F., Kosinka, J., & Dodgson, N. A. (2016). An Evaluation of Local Feature Encodings for Shape Retrieval. In 3DOR: Eurographics Workshop on 3D Object Retrieval, The Eurographics Association Eurographics (European Association for Computer Graphics). DOI: 10.2312/3dor.20161085
  11. Coimbra, D. B., Martins, R. M., Neves, T. T. A. T., Telea, A. C., & Paulovich, F. V. (2016). Explaining three-dimensional dimensionality reduction plots. Information visualization, 15(2), 154-172. DOI: 10.1177/1473871615600010
  12. Messias Martins, R. (2016). Explanatory visualization of multidimensional projections [Groningen]: University of Groningen
  13. Rodrigues Oliveira da Silva, R., Rauber, P. E., Messias Martins, R., Minghim, R., & Telea, A. (2016). Exploring Multidimensional Projections Through Explanatory Maps. Poster session presented at ICT.Open 2016, Amersfoort, Netherlands.
  14. Rodrigues Oliveira da Silva, R., Faccin Vernier, E., Rauber, P., Comba, J. L. D., Minghim, R., & Telea, A. (2016). Metric Evolution Maps: Multidimensional Attribute-driven Exploration of Software Repositories. In VMV16 The Eurographics Association. DOI: 10.2312/vmv.20161343
  15. Barbosa Coimbra, D. (2016). Multidimensional projections for the visual exploration of multimedia data University of Groningen
  16. Mudali, D. (2016). Prediction of neurodegenerative diseases from functional brain imaging data [Groningen]: University of Groningen
  17. Ponjou Tasse, F., Kosinka, J., & Dodgson, N. (2016). Quantitative Analysis of Saliency Models. In SIGGRAPH ASIA 2016 Technical Briefs ACM Press Digital Library. DOI: 10.1145/3005358.3005380
  18. Sobiecki, A. (2016). Skeletonization methods for image and volume inpainting [Groningen]: University of Groningen
  19. Rodrigues Oliveira da Silva, R. (2016). Visualizing multidimensional data similarities: Improvements and applications [Groningen]: University of Groningen
  20. 2015
  21. Buddelmeijer, H., Noorishad, P., Williams, D., Ivanova, M., Roerdink, J. B. T. M., & Valentijn, E. A. (2015). Analyzing Living Surveys: Visualization Beyond the Data Release. In A. R. Taylor, & E. Rosolowski (Eds.), Astronomical Data Analysis Software and Systems XXIV (ADASS XXIV): Proceedings of a conference held 5-9 October 2014 at Calgary (pp. 149-152). (Astronomical Society of the Pacific conference series; Vol. 495). San Francisco: Astronomical Society of the Pacific.
  22. Sobiecki, A., Koehoorn, J., Boda, D., Solovan, C., Diaconeasa, A., Jalba, A., & Telea, A. C. (2015). A New Efficient Method for Digital Hair Removal by Dense Threshold Analysis. In Proceedings 4th World Congress of Dermoscopy (IDS)
  23. Schmitt, W., Sotomayor, J. L., Telea, A., Silva, C. T., & Comba, J. L. D. (2015). A 3D Shape Descriptor Based on Depth Complexity and Thickness Histograms. In 28th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 226-233). IEEEXplore. DOI: 10.1109/SIBGRAPI.2015.51
  24. R. O. da Silva, R., Rauber, P. E., Messias Martins, R., Minghim, R., & Telea, A. (2015). Attribute-based Visual Explanation of Multidimensional Projections. In EuroVA15 The Eurographics Association. DOI: 10.2312/eurova.20151100
  25. Peysakhovich, V., Hurter, C., & Telea, A. (2015). Attribute-driven edge bundling for general graphs with applications in trail analysis. In Proceedings of IEEE Pacific Visualization Symposium (PacificVis) (pp. 39-46). DOI: 10.1109/PACIFICVIS.2015.7156354
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