2022 Tanaboon Tongbuasirilai, Jonas Unger, Christine Guillemot, Ehsan Miandji (2022) A Sparse Non-parametric BRDF Model ACM Transactions on Graphics, Vol. 41, Article 181 Continue to DOI Karin Stacke, Jonas Unger, Claes Lundström, Gabriel Eilertsen (2022) Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications The Journal of Machine Learning for Biomedical Imaging, Vol. 1, Article 023 Param Hanji, Rafal K. Mantiuk, Gabriel Eilertsen, Saghi Hajisharif, Jonas Unger (2022) Comparison of single image HDR reconstruction methods - the caveats of quality assessment SIGGRAPH ’22 Conference Proceedings Daniel Jönsson, Joel Kronander, Jonas Unger, Thomas Schön, Magnus Wrenninge (2022) Direct Transmittance Estimation in Heterogeneous Participating Media Using Approximated Taylor Expansions IEEE Transactions on Visualization and Computer Graphics, Vol. 28, p. 2602-2614 Continue to DOI Rym Jaroudi, Lukáš Malý, Gabriel Eilertsen, Tomas Johansson, Jonas Unger, George Baravdish (2022) Standalone Neural ODEs with Sensitivity Analysis
Tanaboon Tongbuasirilai, Jonas Unger, Christine Guillemot, Ehsan Miandji (2022) A Sparse Non-parametric BRDF Model ACM Transactions on Graphics, Vol. 41, Article 181 Continue to DOI
Karin Stacke, Jonas Unger, Claes Lundström, Gabriel Eilertsen (2022) Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications The Journal of Machine Learning for Biomedical Imaging, Vol. 1, Article 023
Param Hanji, Rafal K. Mantiuk, Gabriel Eilertsen, Saghi Hajisharif, Jonas Unger (2022) Comparison of single image HDR reconstruction methods - the caveats of quality assessment SIGGRAPH ’22 Conference Proceedings
Daniel Jönsson, Joel Kronander, Jonas Unger, Thomas Schön, Magnus Wrenninge (2022) Direct Transmittance Estimation in Heterogeneous Participating Media Using Approximated Taylor Expansions IEEE Transactions on Visualization and Computer Graphics, Vol. 28, p. 2602-2614 Continue to DOI
Rym Jaroudi, Lukáš Malý, Gabriel Eilertsen, Tomas Johansson, Jonas Unger, George Baravdish (2022) Standalone Neural ODEs with Sensitivity Analysis
Three doctoral students to receive Horizon 2020 funding at LiU Three departments will each host a doctoral student funded by the Marie Skłodowska-Curie actions. The research projects deal with using waste heat to produce electricity, perovskites for photonics, and the rendering of computer-generated images.
Success for two online conferences The organisers had planned for 1,000 participants at the two conferences in visualisation in Norrköping, Eurographics and Eurovis. But 2,300 registered, and they presented 100 streamed video sessions that have been viewed nearly 38,000 times. So far.
An AI computer lab using medical images from SCAPIS Scientists plan to use the same technology as that used to create deepfake videos to build AI-generated medical images. The synthesised images will present data from the big SCAPIS study, and will be used for research into AI solutions in healthcare.
Technology for augmented intelligence Augmented intelligence is the first platform in the Vinnova-financed Visual Sweden, based at LiU’s Campus Norrköping. Two new laboratories constitute meeting places in which researchers can collaborate with participating companies.
Exploranation opens science for everyone “We are facing a new scientific paradigm, since advanced fundamental research can now be presented in a manner that visitors understand. We call this ‘Exploranation’ ” says Anders Ynnerman at the Knut and Alice Wallenberg Foundation Symposium.
Computer Graphics and Image Processing The computer graphics and image processing group is driving a number of research projects directed towards the development of theory and methodology for image capture, image analysis and image synthesis.
Department of Science and Technology (ITN) We research and teaches in several technical/scientific disciplines in which our main areas are organic electronics, media, communications and logistics.