The Scandinavian Conference on Image Analysis (SCIA) is a biennial conference on computer vision, image analysis, and pattern recognition. It has been held since 1980 in the scandinavian countries Sweden, Denmark, Norway and Finland. In 2019, SCIA will return to Linköping University, Sweden, where the first conference was held in 1980. However, this time it will be in the nearby city of Norrköping, which hosts the Norrköping Campus of Linköping University.
The conference will be co-located with the Swedish Symposium on Deep Learning (SSDL), which takes place on June 10-11. For more information on SSDL, please see the symposium webpage.
Proceedings of the conference are now online: Springer Lecture Notes in Computer Science
Gold sponsors:
Vironova is a Swedish biotech company bringing new solutions to the field of sub-visible particle characterization. We provide imaging and analysis services, as well as software and instruments for this purpose. Vironova's core technology and expertise is electron microscopy combined with image analysis for detection and characterization of virus and other nano-sized particles and materials. Our main customer basis is working in the highly regulated and quality demanding pharmaceutical industry focusing on drug delivery, gene therapy and vaccine development. Our services are requested both in the R&D, quality control and production phases.
Visual Sweden is an initiative based in Östergötland, Sweden, oriented at promoting innovation and regional growth within the visualization and image analysis fields. Central actors are Region Östergötland, Linköpings Municipality, Norrköpings Municipality, Linköping University, several governmental institutions such as SMHI, NFC and FOI, as well as around 50 smaller, mid-sized and larger companies.
Silver sponsors:
FLIR Systems, Inc. designs, develops, manufactures, markets, and distributes technologies that enhance perception and awareness. We bring innovative sensing solutions into daily life through our thermal imaging, visible-light imaging, video analytics, measurement and diagnostic, and advanced threat detection systems.
Vidhance® by Imint is a video enhancement software platform that transforms a smartphone camera, or in fact, any type of camera into a professional film-making device. The features include Video Stabilization, Noise Reduction, Live Composer and many more high-profile enablers. Imint strives to make the best products possible and Vidhance® currently holds the high score for video stabilization on DxOMark. The products are enjoyed by 70+ million end-users, and smartphone manufacturers such as Huawei, Xiaomi, Oppo and Vivo rely on our products. The qualities of Vidhance® are just as applicable for other industries – drones, smart cameras, IoT or any other area where the camera serves as a key component.
Unibap provides innovative automation solutions on Earth and in space with a vision to create sustainability and better work environments. Unibap offer a range of digitalization services and products for smart plants in the areas of automated quality assurance and flexible automation together with partners like GE Digital, ABB and Intel Corp and customers such as Husqvarna Group and Epiroc. Many solutions leverage Deep Learning, computer vision, robotics, and automation to provide value information for digitized quality assurance, manufacturing process optimization, robot path planning and operations.
Sectra, originally a spin-off from Linköping University, is a world-leading innovator in IT for medical imaging and cybersecurity. Sectra has more than 600 employees and customers in over 60 countries. Current R&D spans across many computer science areas such as artificial intelligence and human-computer-interaction. The global corporate headquarters is in Linköping, Sweden.
Analytic Imaging Diagnostics Arena, AIDA, is a Swedish arena for research and innovation on AI for medical image analysis. Here, academia, healthcare and industry meet to translate AI technology into patient benefit. AIDA assists with financial support, technical resources and competence development. AIDA is an initiative within the Strategic innovation program Medtech4Health, jointly supported by VINNOVA, Formas and the Swedish Energy Agency.
Recorded Future's unique technology collects and analyzes vast amounts of data to deliver relevant cyber threat insights in real time. Our solution aggregates this rich intelligence with any other threat data sources, empowering security teams to collaborate on analysis and delivering intelligence wherever you need it most, including rapid integration with your existing security solutions. We use both machine learning and rule based systems for natural language processing and predictive analytics.
Working at Tobii means being at the heart of innovation. You get to work on really cool projects with passionate, knowledgeable and big-hearted colleagues from all around the world. We use technology to bring a voice to people with speech impairments, to understand human behavior and to revolutionize the way we interact with technology. Founded in 2001, Tobii is the world leader in Eye Tracking but we have only scratched the surface of the possibilities of Eye Tracking! Our headquarter is in Stockholm but we have 13 offices in Europe, North America and Asia where we work diligently to improve our Eye Tracking each and every day.
From factory automation to logistics automation and process automation, SICK is one of the leading sensor manufacturers. As a technology and market leader, SICK provides sensors and application solutions that create the perfect basis for controlling processes securely and efficiently, protecting individuals from accidents, and preventing damage to the environment.
Prof. Laura Leal-Taixé is leading the Dynamic Vision and Learning group at the Technical University of Munich, Germany. She received her Bachelor and Master degrees in Telecommunications Engineering from the Technical University of Catalonia (UPC), Barcelona. She did her Master Thesis at Northeastern University, Boston, USA and received her PhD degree (Dr.-Ing.) from the Leibniz University Hannover, Germany.
During her PhD she did a one-year visit at the Vision Lab at the University of Michigan, USA. She also spent two years as a postdoc at ETH Zurich, Switzerland and one year at the Technical University of Munich. In 2017, she won the Sofja Kovalevskaja Award of 1.65 million euros from the presitgious Humboldt Foundation for her project "socialMaps".
If you ask any student nowadays what tools to use to solve an image recognition task, the most popular answer will be Deep Learning. But the real-world is not static but rather dynamic, and therefore better represented by videos than by still images. It is still an interesting open question how to deal with the temporal redundancy of video frames: shall a Neural Network exploit it or ignore it?
In this talk, I will explore both strategies, i.e., to actually exploit the redundancy in the content of nearby frames, or to ignore it.
In the first work on multiple object tracking, I show how to obtain temporally coherent results while not using temporal information during training. This also alleviates the need for full video annotations. From our recent work on video super resolution, I will present our new temporal discriminator which works in a Generative Adversarial Network training scheme in order to create temporally coherent image details.
Lourdes Agapito holds the position of Professor of 3D Vision in the Department of Computer Science at University College London (UCL). Her research in Computer Vision has focused on the inference of 3D information from the video acquired from a single moving camera. While early research focused on static scenes, attention soon turned to the much more challenging problem of estimating the 3D shape of non-rigid objects (Non-Rigid Structure from Motion, NR-SFM) or complex dynamic scenes where an unknown number of objects might be moving, possibly deforming, independently. Prof. Agapito's research group investigates all theoretical and practical aspects of NRSFM: deformable tracking; dense optical flow estimation and non-rigid video registration; 3D reconstruction of deformable and articulated structure and dense 3D modelling of non-rigid dynamic scenes.
As humans we take the ability to perceive the 3D world around us for granted. From an early age we can grasp an object by adapting our fingers to its 3D shape; or understand our own mother's feelings by interpreting her facial expressions. These tasks require some internal 3D representation of shape, deformations and motion. Building algorithms that can emulate this level of human 3D perception has proved to be an extremely hard task. In this talk I will focus on the acquisition of 3D models of deformable surfaces, such as human faces or bodies, using as input video sequences taken with a single consumer camera. There is now great short-term potential for commercial uptake of this technology. I will share how my research can empower business and society showing some applications to robotics and to AI-driven video synthesis.
Fred Hamprecht holds the Robert-Bosch endowed professorship for Image Analysis and Learning at Heidelberg University. His research interests lie in image processing and machine learning. His main focus is on the development of algorithms to solve interesting problems from the life sciences. Major applications include the tracing of all neurites in a brain, the tracking of all cells in a developing embryo, and quantitative analysis of high-throughput experiments. The group puts particular emphasis on the user-friendly training of such systems, and is actively developing open source libraries and programs such as ilastik. Prof. Hamprecht studied and earned his PhD at the Swiss Federal Institute of Technology (ETH), and became a Professor for Multidimensional Image Processing at Heidelberg University in 2001. He is a co-founder of the Heidelberg Collaboratory for Image Processing (HCI).
Perennial computer vision problems such as image partitioning, instance segmentation or tracking can be reduced to combinatorial graph partitioning problems.
The majority of models developed in this context have relied on purely attractive interactions between graph nodes. To obtain more than a single cluster, it is then necessary to pre-specify a desired number of clusters, or set thresholds.
A notable exception to the above is multicut partitioning / correlation clustering, which accommodates repulsive in addition to attractive interactions, and which automatically determines an optimal number of clusters. Unfortunately, the multicut problem is NP-hard.
In this talk, I will characterize the combinatorial problem and discuss its representations in terms of node or edge labelings. I will discuss greedy algorithms that find approximate solutions, or even exact ones under certain conditions. One algorithm I will discuss is the "mutex watershed" which currently gives the best results on a connectomics challenge.
Joint work with Steffen Wolf, Constantin Pape, Nasim Rahaman, Alberto Bailoni, Ullrich Koethe, Anna Kreshuk.
Tuesday, June 11 | ||
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11.45 - 13.00 | Registration and lunch | The lunch is sponsored by AIDA and SECTRA |
13.00 - 13.15 | Opening | |
13.15 - 14.30 | Oral session 1 | Deep convolutional neural networks |
14.30 - 15.00 | Poster spotlights 1 | |
15.00 - 17.00 | Poster session 1, with coffee | Oral session 1 & poster spotlights 1 |
17.00 - 17.45 | Keynote: Fred Hamprecht | Signed graph partitioning: an important computer vision primitive |
18.00 - | Dome demo, mingle, reception | |
Wednesday, June 12 | ||
09.00 - 10.15 | Oral session 2 | Feature extraction and image analysis |
10.15 - 10.45 | Coffee break | |
10.45 - 12.00 | Oral session 3 | Medical and biomedical image analysis |
12.00 - 13.00 | Lunch | |
13.00 - 13.45 | Keynote: Lourdes Agapito | Capturing vivid 3D models of the world from video |
13.45 - 14.15 | Poster spotlights 2 | |
14.15 - 16.15 | Poster session 2, with coffee | Oral session 2 & 3 & poster spotlights 2 |
16.15 - 17.45 | Oral session 4 | Matching, tracking and geometry |
19.00 - | Conference dinner | |
Thursday, June 13 | ||
09.00 - 09.45 | IAPR keynote: Laura Leal Taixé | Dynamic Scene Understanding - With or without time? |
09.45 - 10.15 | Poster spotlights 3 | |
10.15 - 11.45 | Poster session 3 , with coffee | Oral session 4 & poster spotlights 3 |
11.45 - 12.00 | The future of SCIA/Closing words | |
12.00 - 13.00 | Lunch |
Oral session 1 | Session chair: Anders Heyden |
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Deep Multi-class Adversarial Specularity Removal | John Lin (CEA)*; Mohamed El Amine Seddik (CEA); Mohamed Tamaazousti (CEA); Youssef Tamaazousti (MIT CSAIL); Adrien Bartoli (Université Clermont Auvergne) |
Predicting Novel Views Using Generative Adversarial Query Network | Phong Nguyen (University of Oulu)*; Janne Heikkila (University of Oulu, Finland); Esa Rahtu (Tampere University); Lam Huynh ( University of Oulu) |
CubiCasa5K: A Dataset and an Improved Multi-Task Model for Floorplan Image Analysis | Ahti Kalervo (Aalto University)*; Juha Ylioinas (Aalto University); Markus Häikiö (CubiCasa Inc); Antti Karhu (CubiCasa Inc); Juho Kannala (Aalto University, Finland) |
An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutions | Sercan Türkmen (University of Oulu, Finland)*; Janne Heikkila (University of Oulu, Finland) |
Poster spotlights 1 | Session chair: Ewert Bengtsson |
Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation | Yuxin Hou (Aalto University)*; Arno Solin (Aalto University); Juho Kannala (Aalto University, Finland) |
Fine-Grained Wood Species Identification Using Convolutional Neural Networks | Dmitrii Shustrov (Lappeenranta University of Technology); Tuomas Eerola (Lappeenranta University of Technology)*; Lasse Lensu (Lappeenranta University of Technology); Heikki Kälviäinen (Lappeenranta University of Technology); Heikki Haario (Lappeenranta University of Technology) |
Filtering Specular Reflections by Merging Stereo Images | Michael Plattner (FH OÖ Forschungs & Entwicklungs GmbH)* |
Near Lossless JPEG Compression Based on Masking Effect of Non-Predictable Energy of Image Regions | Mykola Ponomarenko (TUT)*; Karen Egiazarian (TUT, Tampere, Fnland) |
Using a Robotic Arm for Measuring BRDFs | Rasmus Ahrenkiel Lyngby (Technical University of Denmark); Jannik Boll Nielsen ( Technical University of Denmark); Jeppe Revall Frisvad (Technical University of Denmark)*; Anders Bjorholm Dahl (Technical University of Denmark); Henrik Aanæs ( Technical University of Denmark) |
Parametric Model-based 3D Human Shape and Pose Estimation from Multiple Views | Zhongguo Li (Lund University)*; Anders Heyden (Lund University); Magnus Oskarsson (Lund University) |
Efficient Merging of Maps and Detection of Changes | Gabrielle Flood (Lunds Tekniska Högskola)*; David Gillsjö (Lund University); Anders Heyden (LTH); Kalle Åström (Lund University) |
Can SPHARM-based features from automated or manually segmented hippocampi distinguish between MCI and TLE? | Michael Liedlgruber (University of Salzburg); Kevin Butz (Paracelsus Medical University); Yvonne Höller (Paracelsus medical University); Georgi Kuchukhidze (Paracelsus Medical University); Alexandra Taylor (Paraclesus Medical University); Aljoscha Thomschevski (Paracelsus Medical University); Ottavio Tomasi (Paracelsus Medical University); Eugen Trinka (Paracelsus Medical University); Andreas Uhl (University of Salzburg)* |
Oral session 2 | Session chair: Gunilla Borgefors |
Compressed Imaging at Long Range in SWIR | David Gustafsson (Swedish Defence Research Agency (FOI))*; David Bergström (Swedish Defence Research Agency (FOI)); Carl Brännlund ( Swedish Defence Research Agency (FOI)); Andreas Brorsson ( Swedish Defence Research Agency (FOI)) |
Zonohedral Approximation of Spherical Structuring Element for Volumetric Morphology | Patrick Jensen (Danmarks Tekniske Universitet)*; Camilla Trinderup (Technical University of Denmark); Anders Bjorholm Dahl (Technical University of Denmark); Vedrana Andersen Dahl (Technical University of Denmark) |
Image Invariants to Anisotropic Gaussian Blur | Jitka Kostková ( Institute of Information Theory and Automation, CAS)*; Jan Flusser (UTIA, Czech Academy of Sciences); Matěj Lébl (Institute of Information Theory and Automation, CAS) |
Material-Based Segmentation of Objects | Jonathan Dyssel Stets (Technical University of Denmark); Rasmus Ahrenkiel Lyngby (Technical University of Denmark)*; Jeppe Revall Frisvad (Technical University of Denmark); Anders Bjorholm Dahl (Technical University of Denmark) |
Oral session 3 | Session chair: Ingela Nyström |
Fast Cross Correlation for Limited Angle Tomographic Data | Ricardo Sanchez (Max Planck Institute for Biophysics)*; Rudolf Mester (Goethe University Frankfurt); Mikhail Kudryashev (Max Planck Institute for Biophysics) |
Sulcal and cortical features for classification of Alzheimer's disease and mild cognitive impairment | Maciej Plocharski (Aalborg University)*; Lasse Østergaard (Aalborg University) |
On the Effectiveness of Generative Adversarial Networks as HEp-2 Image Augmentation Tool | Tomas Majtner (University of Southern Denmark)*; Buda Bajic (Faculty of Technical Sciences, University of Novi Sad); Joakim Lindblad (Centre for Image Analysis, Department of Information Technology, Uppsala University, Sweden); Natasa Sladoje (Centre for Image Analysis, Department of Information Technology, Uppsala University, Sweden); Victoria Blanes-Vidal (University of Southern Denmark); Esmaeil S. Nadimi (University of Southern Denmark) |
Parameter Selection for Regularized Electron Tomography Without a Reference Image | Yan Guo (Delft University of Technology)*; Bernd Rieger (Delft University of Technology) |
Poster spotlights 2 | Session chair: Vedrana A. Dahl |
Spectral-Spatial Hyperspectral Image Classification Using Cascaded Convolutional Neural Networks | Gurbandurdy Dovletov (University of Duisburg-Essen)*; Tobias Hegemann (University Duisburg-Essen); Josef Pauli (University of Duisburg-Essen) |
Unsupervised Feature Extraction -- a CNN-based Approach | Daniel Trosten (UiT The Arctic University of Norway)*; Puneet Sharma (UiT-The Arctic University of Norway) |
Automatic detection of cervical vertebral landmarks for fluoroscopic joint motion analysis | Ida Marie Groth Jakobsen (Aa); Maciej Plocharski (Aalborg University)* |
Alignment of Building Footprints Using Quasi-Nadir Aerial Photography | Dimitri Bulatov (Fraunhofer IOSB)* |
Evaluation of Feature Detectors, Descriptors and Match Filtering Approaches for Historic Repeat Photography | Ann-Katrin Becker (Universität Osnabrück)*; Oliver Vornberger (Universität Osnabrück) |
Color Normalization of Blood Cell Images | Emmy Sjöstrand (CellaVision)*; Jesper Jönsson (CellaVision) |
Oral session 4 | Session chair: Heikki Kälviäinen |
Combining Depth Fusion and Photometric Stereo for Fine-Detailed 3D Models | Erik Bylow (Lund University)*; Carl Olsson (Lund University, Sweden); Fredrik Kahl (Chalmers); Robert Maier (Technical University of Munich) |
Camera localization by single view query using one circular target | Damien Mariyanayagam (IRIT)*; Pierre Gurdjos (IRIT, ENSEEIHT-INP, Toulouse); Sylvie Chambon (IRIT, ENSEEIHT-INP, Toulouse); Vincent Charvillat (IRIT, ENSEEIHT-INP, Toulouse) |
Global Trifocal Adjustment | Patrik Persson (Lund University)*; Kalle Åström (Lund University) |
A Robust Human Activity Recognition Approach Using OpenPose, Motion Features, and Deep Recurrent Neural Network | Farzan Majeed Noori (University of Oslo)*; Benedikte Wallace (University of Oslo); Md Zia Uddin (UiO); Jim Torresen (University of Oslo) |
Video Frame Interpolation via Cyclic Fine-Tuning and Asymmetric Reverse Flow | Morten Hannemose (Technical University of Denmark)*; Janus Jensen (Technical University of Denmark); Gudmundur Einarsson (Oqton); Jakob Wilm (University of Southern Denmark); Anders Bjorholm Dahl (Technical University of Denmark); Jeppe Revall Frisvad (Technical University of Denmark) |
Poster spotlights 3 | Session chair: Maciej Plocharski |
Assessing Capsule Networks with Biased Data | Bruno Ferrarini (University of Essex)*; Shoaib Ehsan (University of Essex); Adrien Bartoli (Université Clermont Auvergne); Ales Leonardis (University of Birmingham); Klaus D McDonald-Maier (University of Essex) |
Facial Emotion Recognition with Varying Poses and/or Partial Occlusion using Multi-stage Progressive Transfer Learning | Sherin Aly (Alexandria University)* |
Weight Estimation of Broilers in Images using 3D Prior Knowledge | Anders Jørgensen (IHFood)* |
Salient Object Detection With CNNs and Multi-scale CRFs | Yingyue Xu (University of Oulu)*; Xiaopeng Hong (Xi'an Jiaotong University); Guoying Zhao (University of Oulu) |
Dimensionality Reduction for Visualization of Time Series and Trajectories | Pattreeya Tanisaro (University Osnabrueck)*; Gunther Heidemann (Institute of Cognitive Science, University of Osnabrück) |
An RNN-based IMM Filter Surrogate | Stefan Becker (Fraunhofer IOSB)*; Ronny Hug (Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB)); Wolfgang Hübner (Fraunhofer IOSB); Michael Arens (Fraunhofer IOSB) |
Real-Time Tracking-by-Detection in Broadcast Sports Videos | Sigurdur Sverrisson (Ericsson AB)*; Volodya Grancharov (Ericsson AB); Harald Pobloth (Ericsson AB) |
Generating diffusion MRI scalar maps from T1 weighted images using generative adversarial networks | Xuan Gu (Linköping University)*; Markus Nilsson (Lund University); Hans Knutsson (Department of Biomedical Engineering; Center for Medical Image Science and Visualization (CMIV); Linköping University, Sweden); Anders Eklund (Department of Biomedical Engineering; Department of Computer and Information Science, Linköping University, Sweden) |
This prize is awarded by the image analysis societies of Denmark, Finland, Norway and Sweden
The main topics of SCIA 2019 include:
Call for papers can be downloaded here.
The papers can be submitted by following this link. Instructions for the submission will appear in the submission system.
The maximum allowed length for a paper is 12 pages (single column), including references and appendices (if any). Paper submissions are anonymous, i.e. authors should not write their names and affiliations in the submitted paper.
Papers can be submitted in LaTeX or Word format:
Papers accepted for presentation must be resubmitted by April 3 in the submission system. The resubmission must consists of 3 different files:
Authors whose paper has been accepted for presentation in SCIA 2019 must download and compile the Springer copyright form, necessary for the publication in the Springer proceedings. The copyright form must be compiled as follows:
The copyright form must be signed by the corresponding author of the paper and the three boxes in the end must be checked, only if one of the categories apply. Once the form is filled, it must be scanned and converted ina PDF file, which has to be sent along with the files required for the camera ready version of the manuscipt (see above), before April 3.
The copyright form can be downloaded here.
Papers scheduled as orals have an allotted 15mins for their talks. Each talk is followed by a 3min Q&A session, where the next author also prepares to speak. Papers selected for oral presentation also have the option to present a poster, see details above. If you choose to also present a poster, make sure to mention this during the talk, as the talk then serves as your spotlight.
For papers scheduled as posters there are both a poster session and a spotlight. The poster boards are wide enough to accommodate a 1m wide poster. Two common poster sizes that fit are A1 landscape, or A0 portrait. Note that there is no poster printing service at SCIA. Instead we ask you to print your poster beforehand, and bring it to the conference.
Each poster presenter is also offered a poster spotlight presentation before the poster session. A spotlight lasts 3 minutes (with hard cutoff, and no time for questions, save these for the poster session). Use the spotlight to draw interest to your poster, rather than trying to explain all the details. The spotlight presentation (slides in pdf-format, recommended 1 title + 3 slides) must be uploaded latest on June 10 via: https://cmt3.research.microsoft.com/SCIA2019 (opens June 3).
The research papers must neither been published nor submitted for publication elsewhere. Preprints (such as ArXiv) are accepted.
Papers accepted for the SCIA 2019 conference will be published in Lecture Notes in Computer Science Proceedings, Springer. All figures will be in black and white in the printed publication.
Registration to SCIA 2019 and SSDL is now open. Early bird registration is available until April 7.
Register to SCIA 2019, SSDL or SCIA 2019 + SSDL here.
Venue | Type | Early registration (deadline April 7) | Regular registration | On-site registration |
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SCIA | Members | 5000SEK | 6000SEK | 7000SEK |
SCIA | Non-members | 5500SEK | 6500SEK | 7500SEK |
SCIA | Student members | 3600SEK | 4600SEK | 5600SEK |
SCIA | Student non-members | 4100SEK | 5100SEK | 6100SEK |
SSDL + SCIA | Members | 6250SEK | 7250SEK | 8750SEK |
SSDL + SCIA | Non-members | 6750SEK | 7750SEK | 9250SEK |
SSDL + SCIA | Student members | 4850SEK | 5850SEK | 7350SEK |
SSDL + SCIA | Student non-members | 5350SEK | 6350SEK | 7850SEK |
SSDL | All | 1250SEK | 1250SEK | 1750SEK |
SCIA 2019 will be held at Norrköping Visualization Center C at Linköping University, Campus Norrköping located in the old industrial landscape close to Norrköping city center:
Norrköpings Visualiseringscenter C
Kungsgatan 54
602 33 Norrköping
Traveling to Norrköping from outside of Sweden is easy. The closest airport is in the nearby city of Linköping with flights from and to the Schiphol airport in Amsterdam. Linköping airport is accessed to and from Norrköping by taxi or by taking a shuttle or bus to Linköping train station. The local train is operated by Östgötatrafiken leaves from Linköping Resecentrum to Norrköping Resecentrum 3-4 times every hour. Another option is Skavsta airport which operates Ryanair flights from several destinations in Europe and is accessed by frequent airport busses to and from Norrköping. The Arlanda airport in Stockholm can be reached from most major airports and is accessed by several daily direct trains to and from Norrköping.
The SCIA 2019 conference reception on Tuesday June 11 will be held at the Visualization Center and include a mingle and visits to the public exhibitions and the dome theatre. The conference dinner in the evening on Wednesday June 12 will be held at in Östgöta kök's restaurant at Nya Torget close to Norrköping city center.
Directions to the conference dinner:
Östgöta kök
Hospitalsgatan 30
602 27 Norrköping
Norrköping is located approximately 1.5 hours south of Stockholm. From the 17th century to the middle of the 20th century, it was the place of a number of large industries located along the Motala river that floats through the city. The city was a large producer of textiles, and has often been nicknamed "Sweden's Manchester". Today, the former industries have been restorated and transformed into a unique environment that hosts a number of innovative companies, museums, conference center, the Visualization Center C, as well as the Norrköping Campus of Linköping University.
For more information about Norrköping, see for example the experience Norrköping website.
Paper submission opens | December 3, 2018 |
Paper submission deadline | |
Notification of acceptance | March 21, 2019 |
Submission of camera ready manuscript | April 3, 2019 |
Early-bird registration deadline | April 7, 2019 |
Conference | June 11-13, 2019 |
New for this year is that the sponsorship packages cover both SCIA and SSDL. Our sponsorship packages for SCIA and SSDL offer a unique opportunity to:
For more information and booking, please contact Daniel Jönsson.
Name | Affiliation | |
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Adrien Bartoli | adrien.bartoli@gmail.com | Université Clermont Auvergne, France |
Anders Bjorholm Dahl | abda@dtu.dk | Technical University of Denmark |
Anders Heyden | anders.heyden@math.lth.se | Lund University, Sweden |
Atsuto Maki | atsuto@kth.se | KTH Royal Institute of Technology, Sweden |
Carl-Fredrik Westin | westin@bwh.harvard.edu | Harvard University, United States |
Cristina Soguero Ruiz | cristina.soguero@urjc.es | Rey Juan Carlos University |
Domenico Bloisi | bloisi@dis.uniroma1.it | University of Basilicata, Italy |
Einar Heiberg | einar.heiberg@med.lu.se | Lund University, Sweden |
Erkki Oja | erkki.oja@hut.fi | Aalto University, Finland |
Ewert Bengtsson | ewert@cb.uu.se | Uppsala University, Sweden |
Fahad S. Khan | fahad.khan@liu.se | Inception Institute of Artificial Intelligence, United Arab Emirates |
Filip Malmberg | filip.malmberg@it.uu.se | Uppsala University, Sweden |
Francesco Ciompi | francesco.ciompi@radboudumc.nl | Radboud University Medical Center, Netherlands |
Fredrik Kahl | fredrik@maths.lth.se | Lund University, Sweden |
Gunilla Borgefors | gunilla.borgefors@it.uu.se | Uppsala University, Sweden |
Gustau Camps-Valls | gcamps@uv.es | University of Valencia |
Heikki Kälviäinen | heikki.kalviainen@lut.fi | Lappeenranta University of Technology |
Helene Schulerud | helene.schulerud@sintef.no | SINTEF |
Hugues Talbot | hugues.talbot@esiee.fr | Université Paris Est, France |
Ingela Nyström | ingela.nystrom@it.uu.se | Uppsala University, Sweden |
Janne Heikkila | janne.heikkila@ee.oulu.fi | University of Oulu, Finland |
Jens T. Thielemann | jens.t.thielemann@sintef.no | SINTEF |
Joel Kronander | joel.kronander@ninesai.com | Nines |
Joni-Kristian Kamarainen | joni.kamarainen@tut.fi | Tampere University, Finland |
Kalle Åström | kalle@maths.lth.se | Lund University, Sweden |
Kim Pedersen | kimstp@di.ku.dk | University of Copenhagen, Denmark |
Kjersti Engan | kjersti.engan@uis.no | University of Stavanger |
Lasse Østergaard | lasse@hst.aau.dk | Aalborg University |
Lorenzo Livi | lorenz.livi@gmail.com | University of Manitoba, Canada |
Mads Nielsen | madsn@di.ku.dk | University of Copenhagen, Denmark |
Maria Magnusson | maria.magnusson@liu.se | Linköping University, Sweden |
Marius Pedersen | marius.pedersen@ntnu.no | NTNU, Gjovik, Norway |
Natasa Sladoje | natasa.sladoje@it.uu.se | Uppsala University, Sweden |
Robert Jenssen | robert.jenssen@uit.no | UiT - The Arctic University of Norway |
Robin Strand | robin.strand@it.uu.se | Uppsala University, Sweden |
Simone Scardapane | simone.scardapane@uniroma1.it | Sapienza University |
Thomas Moeslund | tbm@create.aau.dk | Aalborg University |
Volker Krueger | volker.krueger@cs.lth.se | Lund University, Sweden |
Walter Kropatsch | krw@prip.tuwien.ac.at | TU Wien, Austria |