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Member Profile

This is "The Multimedia Signal Processing and Security Lab", short WaveLab, website. We are a research group at the Artificial Intelligence and Human Interfaces (AIHI) Department of the University of Salzburg led by Andreas Uhl. Our research is focused on Visual Data Processing and associated security questions. Most of our work is currently concentrated on Biometrics, Media Forensics and Media Security, Medical Image and Video Analysis, and application oriented fundamental research in digital humanities, individualised aquaculture and sustainable wood industry.
 
 Portrait Photo  
Firstname:  Dominik
Lastname:  Söllinger
Room No: 1.13
Telephone: (+43) 662 8044 - 6305
Mail: dsoellinger [at] cs.sbg.ac.at

Dominik Söllinger

 
 

About Me:
I am a PhD student in the WaveLab group.

 
 

Research Interests:

  • Fingerprint biometrics
  • Domain Adaption
  • Deep Learning: Object Detection, Segmentation and Generative Models

 
 

Publications:

    Journal Articles

    1. [Kauba21a   ] Towards Using Police Officers' Business Smartphones for Contactless Fingerprint Acquisition and Enabling Fingerprint Comparison against Contact-Based Datasets Christof Kauba, Dominik Söllinger, Simon Kirchgasser, Axel Weissenfeld, Gustavo Fernández Domínguez, Bernhard Strobl, Andreas Uhl Sensors (Special Issue Biometric Sensing) 21:7, pp. 1-42, 2021
    2. [Soellinger18a   ] Non-reference image quality assessment and natural scene statistics to counter biometric sensor spoofing Dominik Söllinger, Pauline Trung, Andreas Uhl IET Biometrics 7:4, pp. 314-324, 2018

    Conference Papers

    1. [Soellinger22a ] Can point-cloud based neural networks learn fingerprint variability? Dominik Söllinger, Robert Jöchl, Simon Kirchgasser, Andreas Uhl In Proceedings of the IEEE 21th International Conference of the Biometrics Special Interest Group (BIOSIG 2022), pp. 1-8, Darmstadt, Germany, September 14 - September 16, 2022
    2. [Prommegger22a   ] CNN based Finger Region Segmentation for Finger Vein Recognition Bernhard Prommegger, Dominik Söllinger, Georg Wimmer, Andreas Uhl In Proceedings of the 10th International Workshop on Biometrics and Forensics (IWBF'22), pp. 1-6, Salzburg, Austria, April 20 - April 21, 2022
    3. [Soellinger20a  ] Can you really trust the sensor's PRNU? How image content might impact the finger vein sensor identification performance Dominik Söllinger, Luca Debiasi, Andreas Uhl In Proceedings of the 25th International Conference on Pattern Recognition (ICPR), pp. 7782-7789, 2021
    4. [Soellinger21a  ] Optimizing contactless to contact-based fingerprint comparison using simple parametric warping models Dominik Söllinger, Andreas Uhl In 2021 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-7, :, 2021
    5. [Maser19a   ] PRNU-based Finger Vein Sensor Identification in the Presence of Presentation Attack Data Babak Maser, Dominik Söllinger, Andreas Uhl In Proceedings of the Joint ARW/OAGM Workshop 2019 (ARW/OAGM'19)2019
    6. [Soellinger19a  ] PRNU-based finger vein sensor identification: On the effect of different sensor croppings Dominik Söllinger, Babak Maser, Andreas Uhl In Proceedings of the 12th IAPR/IEEE International Conference on Biometrics (ICB'19), pp. 1-8, Crete, Greece, June 4 - June 7, 2019
    7. [Maser19b   ] PRNU-based Detection of Finger Vein Presentation Attacks Babak Maser, Dominik Söllinger, Andreas Uhl In Proceedings of the 7th International Workshop on Biometrics and Forensics (IWBF'19), pp. 1-6, Cancun, Mexico, May 2 - May 3, 2019
    8. [Bhogal17a  ] Non-reference image quality assessment for biometric presentation attack detection (Best Reviewed Papers Session) Amrit Pal Singh Bhogal, Dominik Söllinger, Pauline Trung, Andreas Uhl In Proceedings of the 5th International Workshop on Biometrics and Forensics (IWBF'17), pp. 1-6, Coventry, United Kindom, April 4 - 5, 2017
    9. [Bhogal17b  ] Non-reference image quality assessment for fingervein presentation attack detection Amrit Pal Singh Bhogal, Dominik Söllinger, Pauline Trung, Jutta Hämmerle-Uhl, Andreas Uhl In Proceedings of 20th Scandinavian Conference on Image Analysis (SCIA'17), pp. 184-196, Springer Lecture Notes on Computer Science, 10269, 2017