Marcus Liwicki

9.5k total citations · 1 hit paper
239 papers, 5.0k citations indexed

About

Marcus Liwicki is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Marcus Liwicki has authored 239 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 168 papers in Computer Vision and Pattern Recognition, 90 papers in Artificial Intelligence and 26 papers in Human-Computer Interaction. Recurrent topics in Marcus Liwicki's work include Handwritten Text Recognition Techniques (127 papers), Image Processing and 3D Reconstruction (48 papers) and Natural Language Processing Techniques (44 papers). Marcus Liwicki is often cited by papers focused on Handwritten Text Recognition Techniques (127 papers), Image Processing and 3D Reconstruction (48 papers) and Natural Language Processing Techniques (44 papers). Marcus Liwicki collaborates with scholars based in Germany, Sweden and Switzerland. Marcus Liwicki's co-authors include Horst Bunke, Jürgen Schmidhuber, Alexander Graves, S. George Fernandez, Roman Bertolami, Andreas Dengel, Thomas M. Breuel, Wonmin Byeon, Muhammad Imran Malik and Sheraz Ahmed and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Access.

In The Last Decade

Marcus Liwicki

228 papers receiving 4.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Novel Connectionist System for Unconstrained Handwriting Recognition

2009 1.3k citations Marcus Liwicki, Horst Bunke et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Marcus Liwicki Germany	31	3.4k	1.7k	797	416	413	239	5.0k
Song Wang United States	39	4.5k 1.3×	1.4k 0.8×	719 0.9×	195 0.5×	301 0.7×	334	8.2k
Qiguang Miao China	40	2.4k 0.7×	1.3k 0.8×	1.7k 2.1×	381 0.9×	224 0.5×	246	5.8k
Jun Yu China	44	6.8k 2.0×	3.4k 2.0×	948 1.2×	232 0.6×	551 1.3×	276	9.5k
Ying Shan China	37	4.0k 1.2×	907 0.5×	542 0.7×	196 0.5×	305 0.7×	232	5.7k
Ming-Yu Liu United States	26	6.4k 1.9×	1.2k 0.7×	1.2k 1.5×	197 0.5×	354 0.9×	73	8.2k
Bingbing Ni China	43	5.5k 1.6×	2.9k 1.7×	501 0.6×	324 0.8×	362 0.9×	210	7.6k
Mingkui Tan China	40	5.4k 1.6×	3.3k 1.9×	917 1.2×	209 0.5×	361 0.9×	151	8.1k
Rynson W. H. Lau Hong Kong	37	4.5k 1.3×	786 0.5×	955 1.2×	304 0.7×	149 0.4×	265	6.4k
George Bebis United States	41	4.7k 1.4×	1.2k 0.7×	919 1.2×	733 1.8×	785 1.9×	194	6.9k
Abhinav Gupta United States	35	5.3k 1.6×	3.7k 2.1×	502 0.6×	193 0.5×	289 0.7×	76	7.9k

Countries citing papers authored by Marcus Liwicki

Since Specialization

Citations

This map shows the geographic impact of Marcus Liwicki's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcus Liwicki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcus Liwicki more than expected).

Fields of papers citing papers by Marcus Liwicki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcus Liwicki. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcus Liwicki. The network helps show where Marcus Liwicki may publish in the future.

Co-authorship network of co-authors of Marcus Liwicki

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Liwicki. A scholar is included among the top collaborators of Marcus Liwicki based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcus Liwicki. Marcus Liwicki is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Liwicki, Marcus, et al.. (2026). Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer. Sensors. 26(1). 310–310.

Hashmi, Khurram Azeem, et al.. (2025). Object Detection with Transformers: A Review. Sensors. 25(19). 6025–6025. 1 indexed citations

Mokayed, Hamam, et al.. (2025). Identifying quantum phase transitions with minimal prior knowledge by unsupervised learning. SciPost Physics Core. 8(1).

Kovács, György, Syed Mohammed Shamsul Islam, Tosin Adewumi, et al.. (2024). Seagrass classification using unsupervised curriculum learning (UCL). Ecological Informatics. 83. 102804–102804. 2 indexed citations

Delsing, Jerker, et al.. (2024). AI Concepts for System of Systems Dynamic Interoperability. Sensors. 24(9). 2921–2921. 10 indexed citations

Upadhyay, Richa, Ronald Phlypo, Rajkumar Saini, & Marcus Liwicki. (2024). Sharing to Learn and Learning to Share; Fitting Together Meta, Multi-Task, and Transfer Learning: A Meta Review. KTH Publication Database DiVA (KTH Royal Institute of Technology). 6 indexed citations

Usman, Ali, et al.. (2023). Numerical investigation of thermomechanical behavior of Yttrium barium zirconate-coated aluminum alloy piston in an internal combustion engine. Applied Thermal Engineering. 236. 121603–121603. 17 indexed citations

Saini, Rajkumar, et al.. (2023). Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition. Scientific Data. 10(1). 9 indexed citations

Usman, Ali, et al.. (2023). Machine Learning Composite-Nanoparticle-Enriched Lubricant Oil Development for Improved Frictional Performance—An Experiment. Lubricants. 11(6). 254–254. 4 indexed citations

10.

Hashmi, Khurram Azeem, et al.. (2022). Rethinking Learnable Proposals for Graphical Object Detection in Scanned Document Images. Applied Sciences. 12(20). 10578–10578. 3 indexed citations

11.

Pagani, Alain, et al.. (2022). Three-Dimensional Reconstruction from a Single RGB Image Using Deep Learning: A Review. Journal of Imaging. 8(9). 225–225. 9 indexed citations

12.

Pagani, Alain, et al.. (2022). 3D Reconstruction from a Single RGB Image using Deep Learning: A Review. Preprints.org. 2 indexed citations

13.

Hashmi, Khurram Azeem, et al.. (2022). Mask-Aware Semi-Supervised Object Detection in Floor Plans. Applied Sciences. 12(19). 9398–9398. 4 indexed citations

14.

Usman, Ali, Muhammad Rafiq, Muhammad Saeed, et al.. (2021). Machine Learning Computational Fluid Dynamics. 1–4. 23 indexed citations

15.

Heintz, Fredrik, Amy Loutfi, Johan Axelsson, et al.. (2021). AI COMPETENCE FOR SWEDEN - A NATIONAL LIFE-LONG LEARNING INITIATIVE. EDULEARN proceedings. 1. 2560–2567. 1 indexed citations

16.

Sandin, Fredrik, et al.. (2020). Improving Image Autoencoder Embeddings with Perceptual Loss. KTH Publication Database DiVA (KTH Royal Institute of Technology). 18 indexed citations

17.

Kovács, György, et al.. (2020). Cross-Encoded Meta Embedding towards Transfer Learning. The European Symposium on Artificial Neural Networks. 631–636.

18.

Kovács, György, et al.. (2019). Author Profiling Using Semantic and Syntactic Features : Notebook for PAN at CLEF 2019. SZTE Publicatio Repozitórium (University of Szeged). 2 indexed citations

19.

Otte, Sebastian, et al.. (2015). Learning Recurrent Dynamics using Differential Evolution. The European Symposium on Artificial Neural Networks. 23. 1 indexed citations

20.

Liwicki, Marcus, Alex Graves, Horst Bunke, & Jürgen Schmidhuber. (2007). A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks. Bern Open Repository and Information System (University of Bern). 123 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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