Publication list for
Daniel Soukup
as author or essentially involved person

37 records (2007 - 2019)

The complete list of publications of the Center "Vision, Automation & Control" is available from the publication database beginning with the publication year 2017. The database may but need not necessarily contain publications dated earlier than 2017.

The following list contains presentations with proceedings-entry twice, once as printed contributions, and once as presentations. In general, the total number of records given below is therefore greater than the number shown above.


Books and Book Editorships

1 record:
  1. Tom Van Der Hor, F. Daubner, S. Stolc, D. Soukup, M. Clabian (ed.):
    "Assessment and testing methodologies (PAM4DIS)";
    FRONTEX, Warsaw, Polen, 2019.


Publications in Scientific Journals

7 records:
  1. D. Heiss, R. Huber-Mörk, D. Soukup, H. Penz, B. Lopez Garcia:
    "Demosaicing algorithms for area- and line-scan cameras in print inspection";
    Journal of Visual Communication and Image Representation, 20 (2009), 6; 389 - 398.

  2. R. Huber-Mörk, M. Löhndorf, D. Heiss, K. Mayer, H. Penz, D. Soukup:
    "Fast and Efficient Colour Inspection using Sets of Ellipsoidal Regions";
    Machine Graphics and Vision, 18 (2009), 3; 345 - 361.

  3. D. Soukup, I. Bajla:
    "Robust Object Recognition under Partial Occlusions Using NMF";
    Computational Intelligence and Neuroscience, Vol. 2008 (2008), Article ID 857453; 14 pages.

  4. D. Soukup, U. Bodenhofer, M. Mittendorfer-Holzer, K. Mayer:
    "Semiautomatic Identification of Print Layers from a Sequence of Sample Images: A Case Study from Banknote Print Inspection";
    Image and Vision Computing, doi 10.1016 (2008), - ".

  5. D. Soukup, R. Huber-Mörk:
    "Mobile hologram verificaton with deep learning";
    IPSJ Transactions on Computer Vision and Applications, 9:9 (2017), 1 - 6.

  6. D. Soukup, P. Thanner:
    "Deep Learning der industriellen Inspektion - KI ist kein Allheilmittel";
    Quality Engineering, P3 (2019), P3/2019; 10 - 11.

  7. S. Stolc, D. Soukup, B. Holländer, R. Huber-Mörk:
    "Depth and all-in-focus imaging by a multi-line-scan light-field camera";
    Journal of Electronic Imaging, 23 (2014), 5; 1 - 19.


Publications in Technical Journals

1 record:
  1. D. Soukup, P. Thanner:
    "Lessons in training neutral nets";
    IMAGING & machine vision europe, - (2019), Issue 94; 28 - 30.


Contributions to Books

3 records:
  1. I. Bajla, D. Soukup:
    "Is the Parts-Based Concept of NMF Relevant for Object Recognition Tasks?";
    in: "Machine Learning Research Progress", issued by: Nova Science Publishers; Nova Science Publishers, Hauppauge, NY, USA, 2011, ISBN: 978-1-60456-646-8, 463 - 471.

  2. I. Bajla, D. Soukup, S. Stolc:
    "Occluded Image Object Recognition using Localized Nonnegative Matrix Factorization";
    in: "Object Recognition", K. Lovrecic (ed.); issued by: Intech-Verlag; Intech-Verlag, Rijeka, Kroatien, 2011, ISBN: 978-953-307-222-7, 83 - 118.

  3. R. Huber-Mörk, G. Fernández Domínguez, S. Stolc, D. Soukup, C. Beleznai:
    "Inspection Methods for Metal Surfaces: Image Acquisition and Algorithms for the Characterization of Defects";
    in: "Integrated Imaging and Vision Techniques for Industrial Inspection: Advances and Aplications", issued by: Springer; Springer, London, 2015, ISBN: 978-1-4471-6741-9, 55 - 99.


Contributions to Proceedings

21 records:
  1. D. Antensteiner, S. Stolc, D. Soukup:
    "Single Image Multi-Spectral Photometric Stereo Using a Split U-Shaped CNN";
    Poster: CVPR 2019, Long Beach, California; 06-16-2019 - 06-20-2019; in: "CVPR 2019, Long Beach California", (2019), 481 - 483.

  2. I. Bajla, D. Soukup:
    "A modular non-negative matrix factorizatio for parts-based object recognition using subspace representation";
    Talk: Electronic Imaging 2008, San Jose; 01-27-2008 - 01-31-2008; in: "Electronic Imaging 2008 "Image Processing: Machine Vision Applications" (Volume 6813)", SPIE, (2008), ISSN: 0277-786x; 68130C-1 - 68130C-9.

  3. I. Bajla, D. Soukup:
    "Non-Negative matrix factorization: a study on influence of matrix sparseness and subspace distance metrics on image object recognition";
    Talk: Quality Control by Artificial Vision 2007, Le Creusot, Frankreich; 05-23-2007 - 05-26-2007; in: "SPIE Proceedings "Quality Control by Artificial Vision"", SPE, Vol. 6356 (2007), ISBN: 9780819464514; 635614-1 - 635614-12.

  4. B. Blaschitz, D. Soukup, H. Penz, W. Krattenthaler, R. Huber-Mörk:
    "Testing a Banknote Checking System";
    Talk: 28th International Conference on Testing Software and Systems (ICTSS), Graz; 10-17-2016 - 10-19-2016; in: "Joint Proceedings of the International Workshop on Quality Assurance in Computer Vision and the International Workshop on Digital Eco-Systems", CEUR-WS, Aachen (2016), ISSN: 1613-0073; 6 pages.

  5. R. Huber-Mörk, D. Soukup:
    "Convolutional Neural Networks for Steel Surface Defect Detection from Photometric Stereo Images";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 668 - 677.

  6. R. Huber-Mörk, D. Soukup:
    "Image Super-Resolution for Line Scan Cameras based on a Time Delay Super-Resolution Principle";
    Talk: 6th International Symposium on Image and Signal Processing and Analysis, Salzburg; 09-16-2009 - 09-18-2009; in: "Conference Proceedings of ISPA 2009", IEEE, (2009), ISSN: 1845-5956; 6 pages.

  7. R. Huber-Mörk, D. Soukup, S. Stolc, B. Holländer:
    "Depth Estimation within a Multi-Line-Scan Light-Field Framework";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 471 - 481.

  8. R. Huber-Mörk, S. Stolc, D. Soukup, B. Holländer:
    "Shape from Refocus";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 153 - 162.

  9. T. Pinetz, D. Soukup, R. Huber-Mörk, R. Sablatnig:
    "Using a U-Shaped Neural Network for minutiae extraction trained from refined, synthetic fingerprints";
    Talk: Proceedings of the ÖAGM & ARW Joint Workshop 2017, Vision Automation and Robotics, Wien; 05-10-2017 - 05-12-2017; in: "Proceedings of the ÖAGM & ARW Joint Workshop 2017, Vision Automation and Robotics", Austrian Association for Pattern Recognition and Austrian Robotics Workshop, Verlag der Technischen Universität Graz, Graz, (2017), ISBN: 978-3-85125-524-9; 146 - 151.

  10. T. Pinetz, D. Soukup, T. Pock:
    "On the Estimation of the Wasserstein Distance in Generative Models";
    Talk: 41st DAGM GCPR 2019, Dortmund, Deutschland; 09-10-2019 - 09-13-2019; in: "Pattern Recognition, Proceedings of 41st DAGM German Conference, DAGM GCPR 2019", (2019), ISBN: 978-3-030-33676-9; 156 - 170.

  11. T. Pinetz, D. Soukup, T. Pock:
    "What is optimized in Wasserstein GANs?";
    Keynote Lecture: Computer Vision Winter Workshop 2018, Ceský Krumlov, Cezch Republic; 02-05-2018 - 02-07-2018; in: "Proceedings of the 23rd Computer Vision Winter Workshop", Czech, Vl. 23, Paper-Nummer: 16 (2018), ISBN: 978-80-270-3395-9; Paper ID 16, 9 pages.

  12. T. Pinetz, D. Soukup, J. Ruisz:
    "Actual impact of GAN augmentation on CNN classification performance";
    Talk: International Conference on Pattern Recognition Applications and Methods, Prague; 02-19-2019 - 02-21-2019; in: "Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods", Vol. 1, Paper-Nr. 2 (2019), ISBN: 978-989-758-351-3; 15 - 23.

  13. D. Soukup, R. Huber-Mörk:
    "Cross-Channel Co-Occurence Matrices for Robust Characterization of Surface Disruptions in 2 1/2 D Rail Image Analysis";
    Talk: Advanced Concepts for Intelligent Vision Systems, Brno, CZ; 09-04-2012 - 09-07-2012; in: "Proceedings of Advanced Concepts for Intelligent Vision Systems, Lecture Notes in Computer Science", Springer, Berlin (2012), ISBN: 978-3-642-17687-6; 469 - 474.

  14. D. Soukup, R. Huber-Mörk:
    "Mobile Hologram Verification With Deep Learning";
    Talk: IAPR Int. Conference on Machine Vision and Applications (MVA) 2017, MVA Organization, Japan; 05-08-2017 - 05-12-2017; in: "Proceedings of MVA2017", 5-02 (2017), 1 - 6.

  15. D. Soukup, R. Huber-Mörk:
    "Mobile Hologram Verification With Deep Learning";
    Poster: IAPR Int. Confrence on Machine Vision and Applications (MVA) 2017, MVA Organization, Japan; 05-08-2017 - 05-12-2017; in: "Proceedings of MVA 2017", 5-02 (2017), 1 - 6.

  16. D. Soukup, T. Klatzer, Erich Kobler, K. Hammernik, T. Pock:
    "Trainable Regularization for Multi-frame Superresolution";
    Poster: German Conference on Pattern Recognition (GCPR) 2017, Basel, Switzerland; 09-13-2017 - 09-15-2017; in: "Pattern Recognition. GCPR 2017. Lecture Notes in Computer Science", Springer, Cham, Vol. 10496 (2017), ISBN: 978-3-319-66708-9; 90 - 100.

  17. D. Soukup, T. Pinetz:
    "Reliably Decoding Autoencoders´Latent Spaces for One-Class-Learning Image Inspection Scenarios";
    Talk: OEAGM Workshop 2018, Hall/Tirol; 05-15-2018 - 05-16-2018; in: "Proceedings of the OAGM Workshop 2018, Medical Image Analysis", Peter Roth, Martin Welk, Martin Urschler; Verlag der Technischen Universität Graz, Graz (2018), ISBN: 978-3-85125-603-1; 90 - 93.

  18. D. Soukup, S. Stolc, R. Huber-Mörk:
    "On optimal illumination for DOVID description using photometric stereo";
    Talk: Advanced Concepts for Intelligent Vision Systems, ACIVS 2015, Catania, IT; 10-26-2015 - 10-29-2015; in: "Proceedings of Advanced Concepts for Intelligent Vision Systems. Lecture Notes in Computer Science", Springer, LNCS 7517 (2015), ISBN: 978-3-642-17687-6; Paper ID LNCS 9386, 23 pages.

  19. S. Stolc, R. Huber-Mörk, B. Holländer, D. Soukup:
    "Depth and all-in-focus images obtained by multi-line-scan light-field approach";
    Talk: SPIE-IS&T Electronic Imaging - Image Processing: Machine Vision Applications VII, San Francisco, CA, USA; 02-02-2014 - 02-06-2014; in: "Proceedings of SPIE-IS&T Electronic Imaging - Image Processing: Machine Vision Applications VII", SPIE, Bellingham (2014), ISBN: 978-0-8194-9941-7; 16 pages.

  20. S. Stolc, D. Soukup, R. Huber-Mörk:
    "Analysis of optically variable devices using a photometric light-field approach";
    Talk: IS&T/SPIE Electronic Imaging 2015 - Media Watermarking, Security, and Forensics 2015, San Francisco, CA; 02-08-2015 - 02-12-2015; in: "Media Watermarking, Security and Forensics 2015", SPIE-IS&T, (2015), ISBN: 9781628414998; Paper ID 94090R, 9 pages.

  21. S. Stolc, D. Soukup, R. Huber-Mörk:
    "Invariant characterization of dovid security features using a photometric descriptor";
    Talk: IEEE International Conference on Image Processing, Quebec City, Canada; 09-27-2015 - 09-30-2015; in: "Proceedings of the International Conference on Image Processing", IEEE, (2015), ISBN: 978-1-4244-7994-8; Paper ID IFS-P1.3, 5 pages.


Talks and Poster Presentations at Conferences

24 records:
  1. D. Antensteiner, S. Stolc, D. Soukup:
    "Single Image Multi-Spectral Photometric Stereo Using a Split U-Shaped CNN";
    Poster: CVPR 2019, Long Beach, California; 06-16-2019 - 06-20-2019; in: "CVPR 2019, Long Beach California", (2019), 481 - 483.

  2. D. Antensteiner, S. Stolc, D. Soukup:
    "Surface Normals and Albedo Reconstruction from Single-Shot Images Using a Split U-Net";
    Talk: EMVA Forum 2019, Lyon, France; 09-04-2019 - 09-06-2019.

  3. I. Bajla, D. Soukup:
    "A modular non-negative matrix factorizatio for parts-based object recognition using subspace representation";
    Talk: Electronic Imaging 2008, San Jose; 01-27-2008 - 01-31-2008; in: "Electronic Imaging 2008 "Image Processing: Machine Vision Applications" (Volume 6813)", SPIE, (2008), ISSN: 0277-786x; 68130C-1 - 68130C-9.

  4. I. Bajla, D. Soukup:
    "Non-Negative matrix factorization: a study on influence of matrix sparseness and subspace distance metrics on image object recognition";
    Talk: Quality Control by Artificial Vision 2007, Le Creusot, Frankreich; 05-23-2007 - 05-26-2007; in: "SPIE Proceedings "Quality Control by Artificial Vision"", SPE, Vol. 6356 (2007), ISBN: 9780819464514; 635614-1 - 635614-12.

  5. B. Blaschitz, D. Soukup, H. Penz, W. Krattenthaler, R. Huber-Mörk:
    "Testing a Banknote Checking System";
    Talk: 28th International Conference on Testing Software and Systems (ICTSS), Graz; 10-17-2016 - 10-19-2016; in: "Joint Proceedings of the International Workshop on Quality Assurance in Computer Vision and the International Workshop on Digital Eco-Systems", CEUR-WS, Aachen (2016), ISSN: 1613-0073; 6 pages.

  6. R. Huber-Mörk, D. Soukup:
    "Convolutional Neural Networks for Steel Surface Defect Detection from Photometric Stereo Images";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 668 - 677.

  7. R. Huber-Mörk, D. Soukup:
    "Image Super-Resolution for Line Scan Cameras based on a Time Delay Super-Resolution Principle";
    Talk: 6th International Symposium on Image and Signal Processing and Analysis, Salzburg; 09-16-2009 - 09-18-2009; in: "Conference Proceedings of ISPA 2009", IEEE, (2009), ISSN: 1845-5956; 6 pages.

  8. R. Huber-Mörk, D. Soukup, S. Stolc, B. Holländer:
    "Depth Estimation within a Multi-Line-Scan Light-Field Framework";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 471 - 481.

  9. R. Huber-Mörk, S. Stolc, D. Soukup, B. Holländer:
    "Shape from Refocus";
    Talk: 10th International Symposium on Visual Computing, Las Vegas, NV, USA; 12-08-2014 - 12-10-2014; in: "Advances in Visual Computing, Part 1, Lecture Notes in Computer Science", Springeer, LNCS 8887, Heidelberg (2014), ISBN: 978-3-319-14248-7; 153 - 162.

  10. T. Pinetz, D. Soukup, R. Huber-Mörk, R. Sablatnig:
    "Using a U-Shaped Neural Network for minutiae extraction trained from refined, synthetic fingerprints";
    Talk: Proceedings of the ÖAGM & ARW Joint Workshop 2017, Vision Automation and Robotics, Wien; 05-10-2017 - 05-12-2017; in: "Proceedings of the ÖAGM & ARW Joint Workshop 2017, Vision Automation and Robotics", Austrian Association for Pattern Recognition and Austrian Robotics Workshop, Verlag der Technischen Universität Graz, Graz, (2017), ISBN: 978-3-85125-524-9; 146 - 151.

  11. T. Pinetz, D. Soukup, T. Pock:
    "On the Estimation of the Wasserstein Distance in Generative Models";
    Talk: 41st DAGM GCPR 2019, Dortmund, Deutschland; 09-10-2019 - 09-13-2019; in: "Pattern Recognition, Proceedings of 41st DAGM German Conference, DAGM GCPR 2019", (2019), ISBN: 978-3-030-33676-9; 156 - 170.

  12. T. Pinetz, D. Soukup, T. Pock:
    "What is optimized in Wasserstein GANs?";
    Keynote Lecture: Computer Vision Winter Workshop 2018, Ceský Krumlov, Cezch Republic; 02-05-2018 - 02-07-2018; in: "Proceedings of the 23rd Computer Vision Winter Workshop", Czech, Vl. 23, Paper-Nummer: 16 (2018), ISBN: 978-80-270-3395-9; Paper ID 16, 9 pages.

  13. T. Pinetz, D. Soukup, J. Ruisz:
    "Actual impact of GAN augmentation on CNN classification performance";
    Talk: International Conference on Pattern Recognition Applications and Methods, Prague; 02-19-2019 - 02-21-2019; in: "Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods", Vol. 1, Paper-Nr. 2 (2019), ISBN: 978-989-758-351-3; 15 - 23.

  14. D. Soukup, D. Antensteiner, K. Valentin, R. Huber-Mörk, S. Stolc:
    "High Speed Multi-Line Scan Imaging für Inspection of Tactile Security Features";
    Talk: 2016 Banknote Equipment Manufacturer Conference, Charlotte, USA (invited); 09-21-2016 - 09-22-2016.

  15. D. Soukup, R. Huber-Mörk:
    "Cross-Channel Co-Occurence Matrices for Robust Characterization of Surface Disruptions in 2 1/2 D Rail Image Analysis";
    Talk: Advanced Concepts for Intelligent Vision Systems, Brno, CZ; 09-04-2012 - 09-07-2012; in: "Proceedings of Advanced Concepts for Intelligent Vision Systems, Lecture Notes in Computer Science", Springer, Berlin (2012), ISBN: 978-3-642-17687-6; 469 - 474.

  16. D. Soukup, R. Huber-Mörk:
    "Mobile Hologram Verification With Deep Learning";
    Talk: IAPR Int. Conference on Machine Vision and Applications (MVA) 2017, MVA Organization, Japan; 05-08-2017 - 05-12-2017; in: "Proceedings of MVA2017", 5-02 (2017), 1 - 6.

  17. D. Soukup, R. Huber-Mörk:
    "Mobile Hologram Verification With Deep Learning";
    Poster: IAPR Int. Confrence on Machine Vision and Applications (MVA) 2017, MVA Organization, Japan; 05-08-2017 - 05-12-2017; in: "Proceedings of MVA 2017", 5-02 (2017), 1 - 6.

  18. D. Soukup, T. Klatzer, Erich Kobler, K. Hammernik, T. Pock:
    "Trainable Regularization for Multi-frame Superresolution";
    Poster: German Conference on Pattern Recognition (GCPR) 2017, Basel, Switzerland; 09-13-2017 - 09-15-2017; in: "Pattern Recognition. GCPR 2017. Lecture Notes in Computer Science", Springer, Cham, Vol. 10496 (2017), ISBN: 978-3-319-66708-9; 90 - 100.

  19. D. Soukup, T. Pinetz:
    "Reliably Decoding Autoencoders´Latent Spaces for One-Class-Learning Image Inspection Scenarios";
    Talk: OEAGM Workshop 2018, Hall/Tirol; 05-15-2018 - 05-16-2018; in: "Proceedings of the OAGM Workshop 2018, Medical Image Analysis", Peter Roth, Martin Welk, Martin Urschler; Verlag der Technischen Universität Graz, Graz (2018), ISBN: 978-3-85125-603-1; 90 - 93.

  20. D. Soukup, S. Stolc, R. Huber-Mörk:
    "On optimal illumination for DOVID description using photometric stereo";
    Talk: Advanced Concepts for Intelligent Vision Systems, ACIVS 2015, Catania, IT; 10-26-2015 - 10-29-2015; in: "Proceedings of Advanced Concepts for Intelligent Vision Systems. Lecture Notes in Computer Science", Springer, LNCS 7517 (2015), ISBN: 978-3-642-17687-6; Paper ID LNCS 9386, 23 pages.

  21. D. Soukup, S. Stolc, P. Thanner:
    "Deep learning as Substitute for CRF-Regularization in 3D Image Processing";
    Talk: EMVA Forum 2018, Bologna, Italien; 09-05-2018 - 09-07-2018.

  22. S. Stolc, R. Huber-Mörk, B. Holländer, D. Soukup:
    "Depth and all-in-focus images obtained by multi-line-scan light-field approach";
    Talk: SPIE-IS&T Electronic Imaging - Image Processing: Machine Vision Applications VII, San Francisco, CA, USA; 02-02-2014 - 02-06-2014; in: "Proceedings of SPIE-IS&T Electronic Imaging - Image Processing: Machine Vision Applications VII", SPIE, Bellingham (2014), ISBN: 978-0-8194-9941-7; 16 pages.

  23. S. Stolc, D. Soukup, R. Huber-Mörk:
    "Analysis of optically variable devices using a photometric light-field approach";
    Talk: IS&T/SPIE Electronic Imaging 2015 - Media Watermarking, Security, and Forensics 2015, San Francisco, CA; 02-08-2015 - 02-12-2015; in: "Media Watermarking, Security and Forensics 2015", SPIE-IS&T, (2015), ISBN: 9781628414998; Paper ID 94090R, 9 pages.

  24. S. Stolc, D. Soukup, R. Huber-Mörk:
    "Invariant characterization of dovid security features using a photometric descriptor";
    Talk: IEEE International Conference on Image Processing, Quebec City, Canada; 09-27-2015 - 09-30-2015; in: "Proceedings of the International Conference on Image Processing", IEEE, (2015), ISBN: 978-1-4244-7994-8; Paper ID IFS-P1.3, 5 pages.


Other Talks and Poster Presentations

1 record:
  1. D. Soukup, S. Stolc, R. Huber-Mörk:
    "Analysis of optically variable devices using a photometric light-field approach";
    Talk: Vortrag an der TU Graz, Graz; 06-02-2015.