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Marcus Liwicki
Marcus Liwicki

Marcus Liwicki

Professor and Head of Subject
Luleå University of Technology
Machine Learning
Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
+46 (0)920 491006
A3570 Luleå

Open Minded Research in Machine Learning

Marcus Liwicki received his M.S. degree in Computer Science from the Free University of Berlin, Germany, in 2004, his PhD degree from the University of Bern, Switzerland, in 2007, and his habilitation degree at the Technical University of Kaiserslautern, Germany, in 2011. Currently he is chaired professor at Luleå University of Technology and a senior assistant in the University of Fribourg. His research interests include machine learning, pattern recognition, artificial intelligence, human computer interaction, digital humanities, knowledge management, ubiquitous intuitive input devices, document analysis, and graph matching. From October 2009 to March 2010 he visited Kyushu University (Fukuoka, Japan) as a research fellow (visiting professor), supported by the Japanese Society for the Promotion of Science. In 2015, at the young age of 32, he received the ICDAR young investigator award, a bi-annual award acknowledging outstanding achievements of in pattern recognition for researchers up to the age of 40.

Marcus Liwicki is a member of the IAPR, editor or regular reviewer for international journals, including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Audio, Speech and Language Processing, International Journal of Document Analysis and Recognition (editor), Frontiers of Computer science (editor), Frontiers in Digital Humanities (editor), Pattern Recognition, and Pattern Recognition Letters. He is a member of governing board the International Graphonomics Society and a member of the International Association for Pattern Recognition where he is Vice president of the Technical Committee 6. He chaired several International Workshops on Automated Forensic Handwriting Analysis and the International Workshop on Document Analysis Systems 2014. Furthermore he serves as program committee member and reviewer of various International Conferences and workshops in the area of Computer Vision, Pattern Recognition and Document Analysis as well as Machine Learning and E-Learning. Since 2010 he is the organizer of the discussion groups on the Workshops on Document Analysis and Recognition

Marcus Liwicki gave a number of invited talks at several international workshops, universities, and companies. He also gave several tutorials on IAPR conferences. Marcus Liwicki is a co-author of the book "Recognition of Whiteboard Notes – Online, Offline, and Combination", published by World Scientific in October 2008.--> He has more than 200 publications, including more than 20 journal papers, and excluding more than 20 publications which currently undergo the review stage or will soon be published.


Special Studies in Machine Learning (D7051E), link
Advanced Data Mining (D7043E), link
Neural networks and learning machines (D7046E), link
Advanced deep learning (D7047E), link
Introduction to Artificial Intelligence (D0030E), link

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Conference paper

A Blended Attention-CTC Network Architecture for Amharic Text-image Recognition (2021)

Belay. B, Habtegebrial. T, Liwicki. M, Belay. G, Stricker. D
Part of: Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM), s. 435-441, SciTePress, 2021
Article in journal

Anomaly Detection in Natural Scene Images based on enhanced Fine-Grained Saliency and Fuzzy Logic (2021)

Mokayed. H, Shivakumara. P, Saini. R, Liwicki. M, Chee Hin. L, Pal. U
IEEE Access
Article in journal

Artificial Neural Network Architecture for Prediction of Contact Mechanical Response (2021)

Kalliorinne. K, Larsson. R, Pérez-Ràfols. F, Liwicki. M, Almqvist. A
Frontiers in Mechanical Engineering, Vol. 6
Article in journal

Cascade Network with Deformable Composite Backbone for Formula Detection in Scanned Document Images (2021)

Hashmi. K, Pagani. A, Liwicki. M, Stricker. D, Afzal. M
Applied Sciences, Vol. 11, nr. 16
Article, review/survey

Current Status and Performance Analysis of Table Recognition in Document Images with Deep Neural Networks (2021)

Hashmi. K, Liwicki. M, Stricker. D, Afzal. M, Afzal. M, Afzal. M
Part of: IEEE Access