The 41st Swedish Symposium on Image Analysis
The 7th Swedish Symposium on Deep Learning
LTU, Luleå, Sweden, March 11-13, 2024

about SSBA/SSDL 2024

We celebrate the 41st anniversary of the Swedish Symposium on Image Analysis (SSBA) this year. It is co-located with the 7th Swedish Symposium on Deep Learning (SSDL). The event takes place at Luleå University of Technology, Luleå, Sweden, which is home to the spectacular Northern Lights.

The SSBA symposium is the premier Swedish event where researchers, industrial professionals and students gather to learn about the recent developments in the areas of image processing, computer vision, pattern recognition and related fields. SSBA 2024 will feature keynote speakers, and oral presentations and posters of submitted papers.

SSDL is an important Swedish forum for leading research groups in industry and academia to meet and discuss the latest trends and developments in deep learning and related areas. SSDL 2024 will feature invited talks by leading researchers in deep learning as well as oral and poster presentations of submitted papers and abstracts.


Elisa Barney

Keynote: Historical Document Analysis and the Humanities

Elisa Barney

Professor , Luleå University of Technology

Elisa Barney Smith is a professor at Luleå University of Technology (LTU). She received her Ph.D. in Electrical, Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, NY, USA. Professor Barney’s main research interests are image processing and machine learning. She applies these primarily to document imaging. Here is her homepage

Robert Jenssen

Keynote: XAI for representation learning


The field of eXplainable AI (XAI) has received tremendous attention in recent years. Most work in the XAI literature focus on providing input attributions in some form. In computer vision, for instance, attribution maps are created by methods that aim to highlight the pixels that were relevant for a certain image classification by e.g. a neural network. However, basically nobody has tried to explain representations. Representation learning, for instance via self-supervised learning, is key to any machine learning system. This talk will outline a new proposed framework called RELAX to provide XAI for representation learning in computer vision.

Robert Jenssen

Director, Visual Intelligence

Robert Jenssen is a Professor at UiT, Machine Learning Group and the Director, Visual Intelligence. Visual Intelligence is a Centre for Research-based Innovation (SFI) funded by the Research Council of Norway and a consortium of private and public partners. We are at the international forefront in deep learning research for complex image analysis. Here is his homepage

Seiichi Uchida

Keynote: "beyond 100%" - Open research in Document Analysis


Document image analysis has a long research history and thus is considered as a mature research field. In fact, recent OCR (optical character reader) systems can indeed recognize various document images, such as scene texts and decorated font images, with very high accuracy, because of deep learning technologies and large-scale datasets. It should be emphasized that this situation does not indicate the shrinkage of the research. Instead, it indicates that we can start new research by utilizing the highly-accurate OCR systems and deep learning technologies. In my talk, I will introduce several new research trials that use the textual information collected by the recent OCRs as well as trials that are first enabled by deep learning technologies.

Seiichi Uchida

Professor (Distinguished Professor of Kyushu University)

Seiichi Uchida received B.E. and M.E. and Dr. Eng. degrees from Kyushu University in 1990, 1992 and 1999, respectively. From 1992 to 1996, he joined SECOM Co., Ltd., Japan. Currently, he is a distinguished professor at Kyushu University, Japan. His research interests include pattern recognition and image processing. He received 2007 IAPR/ICDAR Best Paper Award and many international and domestic awards. Here is his homepage


Keynote: Diagnosis and prognostication in medical imaging using AI


The field of medical image analysis is making great strides in the era of deep learning (DL), with a wide range of problems being addressed using such techniques. Two considerable limitations to the use of DL in medical imaging is the lack of annotated data needed for supervised learning, and the oftentimes low level of explainability and missing uncertainty estimation of DL predictions. In my presentation, I will talk about the use of weakly labeled data for cancer diagnosis and prognostication, and ways to improve prognostication with new survival modelling approaches. Furthermore, I will talk about the combination of DL and rule-based approaches for explainability and uncertainty estimation in the detection of bone structures in medical images.

Ida Häggström

Associate Professor, Signal Processing and Biomedical Engineering, Electrical Engineering

Ida's research is focused on medical image analysis using machine learning techniques. She collaborates closely with medical doctors on projects to diagnose, predict and prognosticate different diseases, mainly cancer. She works mainly with images from positron emission tomography (PET), but also computed tomography (CT) and magnetic resonance imaging (MR). Here is her homepage

Practical Info: Please use a dark/black background for your presentation slides, as study has shown this to be better for the eyes.
Call for contributions by mail: (1) Short tutorial submissions - suggest a topic you would like to give a short (20mins) tutorial on for the PhD-student day.
(2) Bring your own problem – pitch short abstracts for 3 minutes about a problem or method your would like to share with the SSBA/SSDL audience.
Deadline: 28 February. Please, use the same template as for abstract submissions below (or Word) and mail it to the above address or
Monday, March 11  Location
7.30 Registration LKAB (A117)
8.00 - 10.00 PhD student day
Chair: Marcus Liwicki
LKAB (A117)
10.00 - 10.30 Fika break (only for PhD students)
10.30 - 11.00 PhD student day
Chair: Marcus Liwicki
Short tutorials LKAB (A117)
11.00 - 12.00 PhD student day Visit to the robotics lab and mingle
12.00 - 13.00 Lunch (and SSBA board meeting - A110) Stuk (C hus)
13.00 - 13.20 Opening: Marcus Liwicki LKAB (A117)
13.20 - 14.20 Keynote: Seiichi Uchida
Chair: Marcus Liwicki
"beyond 100%" - Open research in Document Analysis LKAB (A117)
14.20 - 14.40 Bring-Your-Own-Problem Pitches
Chair: Marcus Liwicki
Beyond traditional >> Spherical neurons >> Automatic
production quality >> Reconstructing Hadron
LKAB (A117)
14.40 - 15.00 Fika break
15.00 - 15.40 SSDL Pitches: Cut-and-Paste >> Generative Models >> Instruction >> EmergAI >> Deep Ontology >> Generative AI >>
Cloth-Splatting >> Exploring Temporal >> Intermodal >> GMSF >> Enhancing >> In Defense >> Enabling Diffusion
Chair: Tosin Adewumi
15.40 - 16.40 SSDL Poster session LKAB corridor
17.30 Light dinner starts LKAB corridor
18.00 - 19.00 SSBA Annual General Meeting Start of SSBA LKAB (A117)
Tuesday, March 12    
8.00 - 9.00 Keynote: Ida Häggström
Chair: Tosin Adewumi
Diagnosis and prognostication in medical imaging using AI LKAB (A117) 
9.00 - 10.15
SSBA oral session 1
Chair: György Kovács
(1) 9.00 - 9.25: Computing the Lipschitz constant needed for fast scene
recovery from CASSI measurements
(2) 9.25 - 9.50: Learned Trajectory Embedding for Subspace Clustering
(3) 9.50 - 10.15: MOoSE: Multi-Orientation Sharing Experts for Open-set
Scene Text Recognition
LKAB (A117)  
10.15 - 10.30 Fika break
10.30 - 12.00 SSBA oral session 2
Chair: Simon Corbillé
(4) 10.30 - 11.00: Navigating Seasonal Changes: Neural Radiance Fields
for Satellite Image-Based 3D Reconstruction
(5) 11.00 - 11.30: Adaptive Sampling for BRDF Acquisition
(6) 11.30 - 12.00: Steerers
LKAB (A117)  
12.00 - 13.00 Lunch Stuk (C hus)
13.00 - 14.00 Keynote: Elisa Barney
Chair: Homam Mokayed
Historical Document Analysis and the Humanities LKAB (A117)
14.00 - 14.20 Short Talk: George Nikolakopoulos
Chair: Homam Mokayed
Robotics and AI group in Luleå LKAB (A117)
14.20 - 14.40 Bring-Your-Own-Problem Pitches
Chair: Homam Mokayed
Interoperable Visual Localization >> Denoising atomically LKAB (A117)
14.40 - 15.00 Fika break
15.00 - 18.00 Social event Underground mining lab in
Mjölkluddsberget & Teknikenshus
18.00 - 21.00 Dinner & Award
(Most Industry-Relevant Paper)
Wednesday, March 13  
8.00 - 9.00 Keynote: Robert Jenssen
Chair: Tommaso Dorigo
XAI for representation learning LKAB (A117) 
9.00 - 10.15 SSBA oral session 3
Chair: Chang Liu
(7) 9.00 - 9.25: Robust AI based prostate cancer grading exceeding
human performance
(8) 9.25 - 9.50: Comparing Diffusion Models and GANs in Synthesizing Brain
MRI and Chest X-Ray Images: A Focus on Memorization Risks
(9) 9.50 - 10.15: Recognising Swedish Handwritten Stenography
LKAB (A117)  
10.15 - 10.30 Fika break
10.30 - 12.00 SSBA oral session 4
Chair: Yushan Zhang
(10) 10.30 - 11.00: Geometry from a Single Motion Blurred Image
(11) 11.00 - 11.30: Classifying femur fractures using federated learning
(12) 11.30 - 12.00: Federated training of segmentation models for
radiotherapy treatment planning
LKAB (A117)  
12.00 - 13.00 Lunch Stuk (C hus)
13.00 - 14.40 Industry session | Panel discussion
Chair: Marcus Liwicki
The progress of AI adoption in Sweden, Challenges and Next teps LKAB (A117)
The PhD student day includes a guided tour to the Robotics lab and is the perfect oppurtunity for PhD students to network and get to know peers within the community.


You can download the proceedings (based on authors' permission)  here .

Important Dates

  • January 10, 2024

    Paper/Abstract submission & Registration opens

  • January 30, 2024

    Early-bird registration deadline

  • February 12, 2024

    Paper submission deadline

  • March 5, 2024

    Late registration deadline

  • March 11, 2024 (9-lunch)

    PhD student day

  • March 11-13, 2024



We invite researchers from academy and industry to contribute to our joint symposium. The symposium is meant to be a snapshot of interesting activity in Sweden, and thus we welcome previously published material, and material that you plan to publish elsewhere. Contributions to SSDL and SSBA will not be made openly available online.

SSBA submissions

SSBA is open for (the usual) short papers (up to 6 pages, including references) on any topic in image analysis, computer vision or pattern recognition. Contributions will primarily be presented orally.
A template with paper formatting is available here.
SSBA short papers are submitted by email, to:

SSDL submissions

SSDL is open for extended abstracts (2-3 pages, including references) on any topic of interest within AI, machine learning or deep learning. The contributions will primarily be presented as posters (portrait format with a maximum width of 80 cm). A number of the submitted contributions will be chosen for oral presentation alongside the keynote talks at the symposium.
Please use the same template as for the SSBA short papers.
SSDL extended abstracts are submitted by email, to:


Please, register in advance. There will be no registration on site.

Registration fees (excluding VAT, includes lunch, fika, social event & dinner on Tuesday)

TypeEarly bird
(deadline January 30)
Regular registration
(deadline March 5)
Members2000 SEK2400 SEK
Students1500 SEK1900 SEK

Prices are excluding VAT.

General registration


SSBA/SSDL 2024 will be held at Luleå University of Technology (LTU), Luleå.

Click on the map to search for a specific room. House A is the location.
LTU Computer Phone

Practical Information and Public Transportation

It is very easy to plan your journey and transportation in Luleå. LLT has an app called journey planner and there you can plan and book your bus tickets. Tickets must be purchased before boarding the bus. You can travel with a bus pass or a mobile ticket. Types of tickets: 72-hour ticket is the perfect choice for when you're just visiting Luleå for a few days. This pass will allow you to take unlimited trips for 72 hours.

Bus numbers 4, 5, 6 and 7 get to LTU from the city center. Bus 4 gets to LTU from the airport. These buses stop at "Universitetsentren" (the closest stop), "Porsön" and "Kårhusvägen", which are all within 2 minutes walk to the location in the University. You may download the LLT app to buy the ticket of your choice.

Attractions in Luleå

Norra hamn, ice breaker, Gammaelstad Church Town. For further information, you may refer to this link



A. Exhibitor, SEK 20,000

  1. Demonstration and exhibition space at your disposal.
  2. Free registration for 1 company representative (incl. accommodation).


B. Silver sponsorship, SEK 15,000

  1. Your logo on the symposium website.
  2. Public acknowledgement of your support during the conference.
  3. Your company is mentioned with a logo in the conference program sheet.


C. Gold sponsorship, SEK 30,000

  1. Your logo on the symposium website.
  2. Public acknowledgement of your support during the conference.
  3. Your company is mentioned with a logo in the conference program sheet.
  4. Demonstration and exhibition space at your disposal.
  5. Free registration for 1 company representative (incl. accommodation).
  6. You will have the opportunity to contribute material to our goodie bags.
  7. Guaranteed time for presentation during the industry session.
For more information and booking, please contact Tosin Adewumi.


General Chair

Marcus Liwicki (LTU) 

Finance Chair

Lama Alkhaled (LTU) 

Program Chairs

Homam Mokayed (LTU)
Foteini Simistira Liwicki (LTU)
Amanda Berg (Linköping University)
Tosin Adewumi (LTU)  

Local Arrangements Chairs

Lama Alkhaled (LTU)
Tosin Adewumi (LTU) 

Publicity Chair

Marcus Liwicki (LTU) 

PhD Student Day Chair

Marcus Liwicki (LTU)
Pedro Alonso (LTU)