Carsten Haubold

4.5k total citations · 1 hit paper
10 papers, 2.0k citations indexed

About

Carsten Haubold is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Molecular Biology. According to data from OpenAlex, Carsten Haubold has authored 10 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 4 papers in Biophysics and 3 papers in Molecular Biology. Recurrent topics in Carsten Haubold's work include Advanced Vision and Imaging (5 papers), Computer Graphics and Visualization Techniques (3 papers) and Cell Image Analysis Techniques (3 papers). Carsten Haubold is often cited by papers focused on Advanced Vision and Imaging (5 papers), Computer Graphics and Visualization Techniques (3 papers) and Cell Image Analysis Techniques (3 papers). Carsten Haubold collaborates with scholars based in Germany, United States and Switzerland. Carsten Haubold's co-authors include Martin Schiegg, Fred A. Hamprecht, Ullrich Koethe, Anna Kreshuk, Stuart Berg, Chong Zhang, Thorben Kroeger, Dominik Kutra, Kemal Eren and Bernhard X. Kausler and has published in prestigious journals such as Bioinformatics, Nature Methods and IEEE Transactions on Medical Imaging.

In The Last Decade

Carsten Haubold

10 papers receiving 2.0k citations

Hit Papers

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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

Countries citing papers authored by Carsten Haubold

Since Specialization

Citations

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

Fields of papers citing papers by Carsten Haubold

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carsten Haubold

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

All Works

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10 of 10 papers shown

#	Work	Indexed citations
1	Geospatial Analytics Extension for KNIME 2023 ·SoftwareX ·Lingbo Liu, Xiaokang Fu, Tobias Kötter, (unknown), Carsten Haubold, Weihe Wendy Guan, Shuming Bao, Fahui Wang	3
2	ilastik: interactive machine learning for (bio)image analysis breakdown → 2019 ·Nature Methods ·Stuart Berg, Dominik Kutra, Thorben Kroeger, Christoph Straehle, Bernhard X. Kausler, Carsten Haubold, Martin Schiegg, Janez Aleš, Thorsten Beier, (unknown), Kemal Eren, (unknown), (unknown), Fynn Beuttenmueller, Adrian Wolny, Chong Zhang, Ullrich Koethe, Fred A. Hamprecht, Anna Kreshuk	1844
3	DiversePathsJ: diverse shortest paths for bioimage analysis 2017 ·Bioinformatics ·Virginie Uhlmann, Carsten Haubold, Fred A. Hamprecht, Michaël Unser	2
4	Segmenting and Tracking Multiple Dividing Targets Using ilastik 2016 ·Advances in anatomy, embryology and cell biology ·Carsten Haubold, Martin Schiegg, Anna Kreshuk, Stuart Berg, Ullrich Koethe, Fred A. Hamprecht	35
5	Network Flow Integer Programming to Track Elliptical Cells in Time-Lapse Sequences 2016 ·IEEE Transactions on Medical Imaging ·Engin Türetken, Xinchao Wang, Carlos Becker, Carsten Haubold, Pascal Fua	45
6	Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models 2015 ·Martin Schiegg, (unknown), Carsten Haubold, Steffen Wolf, Ullrich Koethe, Fred A. Hamprecht	1
7	Graphical model for joint segmentation and tracking of multiple dividing cells 2014 ·Bioinformatics ·Martin Schiegg, Philipp Hanslovsky, Carsten Haubold, Ullrich Koethe, Lars Hufnagel, Fred A. Hamprecht	57
8	Ambient point clouds for view interpolation 2010 ·Michael Goesele, Jens Ackermann, Simon Fuhrmann, Carsten Haubold, (unknown), Drew Steedly, Richard Szeliski	12
9	Ambient point clouds for view interpolation 2010 ·ACM Transactions on Graphics ·Michael Goesele, Jens Ackermann, Simon Fuhrmann, Carsten Haubold, (unknown), Drew Steedly, Richard Szeliski	38
10	Ambient point clouds for view interpolation 2010 ·ACM Transactions on Graphics ·Michael Goesele, Jens Ackermann, Simon Fuhrmann, Carsten Haubold, (unknown), (unknown)	7

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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