Martin Schiegg

3.9k total citations · 1 hit paper
10 papers, 2.1k citations indexed

About

Martin Schiegg is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biophysics. According to data from OpenAlex, Martin Schiegg has authored 10 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Biophysics. Recurrent topics in Martin Schiegg's work include Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers) and Time Series Analysis and Forecasting (3 papers). Martin Schiegg is often cited by papers focused on Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (3 papers) and Time Series Analysis and Forecasting (3 papers). Martin Schiegg collaborates with scholars based in Germany, United States and Netherlands. Martin Schiegg's co-authors include Fred A. Hamprecht, Ullrich Koethe, Carsten Haubold, Bernhard X. Kausler, Anna Kreshuk, Stuart Berg, Chong Zhang, Thorben Kroeger, Dominik Kutra and Kemal Eren and has published in prestigious journals such as Bioinformatics, Nature Methods and IEEE Transactions on Medical Imaging.

In The Last Decade

Martin Schiegg

10 papers receiving 2.0k 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.

ilastik: interactive machine learning for (bio)image analysis

2019 1.8k citations Stuart Berg, Dominik Kutra et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Martin Schiegg Germany	7	784	692	233	226	167	10	2.1k
Bernhard X. Kausler Germany	6	781 1.0×	645 0.9×	261 1.1×	220 1.0×	142 0.9×	6	2.1k
Thorsten Beier Germany	8	747 1.0×	615 0.9×	227 1.0×	221 1.0×	134 0.8×	15	2.0k
Carsten Haubold Germany	7	771 1.0×	670 1.0×	232 1.0×	220 1.0×	159 1.0×	10	2.0k
Ullrich Koethe Germany	12	830 1.1×	790 1.1×	239 1.0×	234 1.0×	168 1.0×	26	2.3k
Tim Wang China	2	877 1.1×	638 0.9×	205 0.9×	173 0.8×	174 1.0×	5	1.7k
Michalis Michaelos United States	8	887 1.1×	645 0.9×	211 0.9×	174 0.8×	175 1.0×	8	1.9k
Thorben Kroeger Germany	5	742 0.9×	604 0.9×	225 1.0×	214 0.9×	123 0.7×	5	1.9k
Dominik Kutra Germany	3	738 0.9×	605 0.9×	224 1.0×	222 1.0×	136 0.8×	6	1.9k
Fynn Beuttenmueller Germany	2	740 0.9×	645 0.9×	229 1.0×	242 1.1×	137 0.8×	2	1.9k
Kemal Eren Türkiye	10	1.0k 1.3×	586 0.8×	242 1.0×	237 1.0×	121 0.7×	53	2.7k

Countries citing papers authored by Martin Schiegg

Since Specialization

Citations

This map shows the geographic impact of Martin Schiegg'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 Martin Schiegg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Schiegg more than expected).

Fields of papers citing papers by Martin Schiegg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Schiegg. 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 Martin Schiegg. The network helps show where Martin Schiegg may publish in the future.

Co-authorship network of co-authors of Martin Schiegg

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Schiegg. A scholar is included among the top collaborators of Martin Schiegg 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 Martin Schiegg. Martin Schiegg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Schiegg, Martin, et al.. (2020). Relational Generalized Few-Shot Learning. 1 indexed citations

2.

Berg, Stuart, Dominik Kutra, Thorben Kroeger, et al.. (2019). ilastik: interactive machine learning for (bio)image analysis. Nature Methods. 16(12). 1226–1232. 1844 indexed citations breakdown →

3.

Kausler, Bernhard X., et al.. (2018). Time series anomaly detection based on shapelet learning. Computational Statistics. 34(3). 945–976. 32 indexed citations

4.

Haubold, Carsten, Martin Schiegg, Anna Kreshuk, et al.. (2016). Segmenting and Tracking Multiple Dividing Targets Using ilastik. Advances in anatomy, embryology and cell biology. 219. 199–229. 35 indexed citations

5.

Schiegg, Martin, et al.. (2015). Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models. 394–398. 1 indexed citations

6.

Diego, Ferran, et al.. (2014). Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning. 2736–2743. 19 indexed citations

7.

Schiegg, Martin, Philipp Hanslovsky, Carsten Haubold, et al.. (2014). Graphical model for joint segmentation and tracking of multiple dividing cells. Bioinformatics. 31(6). 948–956. 57 indexed citations

8.

Lou, Xinghua, Martin Schiegg, & Fred A. Hamprecht. (2014). Active Structured Learning for Cell Tracking: Algorithm, Framework, and Usability. IEEE Transactions on Medical Imaging. 33(4). 849–860. 21 indexed citations

9.

Schiegg, Martin, Philipp Hanslovsky, Bernhard X. Kausler, Lars Hufnagel, & Fred A. Hamprecht. (2013). Conservation Tracking. 2928–2935. 43 indexed citations

10.

Schiegg, Martin, Marion Neumann, & Kristian Kersting. (2012). Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 1002–1011. 3 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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