Karsten Roth

3.3k total citations · 1 hit paper
17 papers, 810 citations indexed

About

Karsten Roth is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Oncology. According to data from OpenAlex, Karsten Roth has authored 17 papers receiving a total of 810 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Oncology. Recurrent topics in Karsten Roth's work include Domain Adaptation and Few-Shot Learning (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Neutropenia and Cancer Infections (3 papers). Karsten Roth is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Neutropenia and Cancer Infections (3 papers). Karsten Roth collaborates with scholars based in Germany, United States and United Kingdom. Karsten Roth's co-authors include Joaquin Zepeda, Peter Gehler, Bernhard Schölkopf, Thomas Brox, Latha Pemula, Björn Ommer, Biagio Brattoli, J. Jansén, Herman W. Barkema and Cindy L. Adams and has published in prestigious journals such as Blood, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Dairy Science.

In The Last Decade

Karsten Roth

16 papers receiving 790 citations

Hit Papers

Towards Total Recall in Industrial Anomaly Detection 2022 2026 2023 2024 2022 200 400 600
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.

  1. Towards Total Recall in Industrial Anomaly Detection
    2022 622 citations Karsten Roth, Latha Pemula et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karsten Roth Germany 8 531 232 195 134 85 17 810
Joaquin Zepeda France 5 488 0.9× 203 0.9× 195 1.0× 134 1.0× 85 1.0× 9 676
Latha Pemula Germany 1 469 0.9× 155 0.7× 194 1.0× 134 1.0× 85 1.0× 2 622
Vitjan Zavrtanik Slovenia 7 696 1.3× 259 1.1× 262 1.3× 199 1.5× 126 1.5× 9 900
Xingyu Li Canada 14 553 1.0× 421 1.8× 95 0.5× 115 0.9× 225 2.6× 57 1.2k
Lukas Ruff Germany 5 518 1.0× 93 0.4× 42 0.2× 193 1.4× 56 0.7× 10 641
Lucas Deecke United Kingdom 2 422 0.8× 76 0.3× 39 0.2× 174 1.3× 51 0.6× 2 488
Jongyoun Noh South Korea 3 530 1.0× 316 1.4× 43 0.2× 335 2.5× 33 0.4× 5 696
Giuseppe Di Leo Italy 16 191 0.4× 216 0.9× 109 0.6× 49 0.4× 35 0.4× 63 810
Zhongyi Pei China 5 481 0.9× 305 1.3× 21 0.1× 73 0.5× 185 2.2× 8 856
Barath Narayanan Narayanan United States 16 289 0.5× 171 0.7× 51 0.3× 167 1.2× 46 0.5× 33 746

Countries citing papers authored by Karsten Roth

Since Specialization
Citations

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

Fields of papers citing papers by Karsten Roth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karsten Roth

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

All Works

17 of 17 papers shown
1.
Selmaj, Krzysztof, Karsten Roth, Rafał Derlacz, et al.. (2024). Introducing the Biosimilar Paradigm to Neurology: The Totality of Evidence for the First Biosimilar Natalizumab. BioDrugs. 38(6). 755–767. 5 indexed citations
2.
Akata, Zeynep, Samuel Albanie, Matthias Bethge, et al.. (2024). A Practitioner's Guide to Real-World Continual Multimodal Pretraining. 133801–133845.
3.
Petch, Jeremy, Walter Nelson, Karsten Roth, et al.. (2023). Nailfold capillaroscopy and deep learning in diabetes. Journal of Diabetes. 15(2). 145–151. 17 indexed citations
4.
Hemmer, Bernhard, Heinz Wiendl, Karsten Roth, et al.. (2023). Efficacy and Safety of Proposed Biosimilar Natalizumab (PB006) in Patients With Relapsing-Remitting Multiple Sclerosis. JAMA Neurology. 80(3). 298–298. 21 indexed citations
5.
Roth, Karsten, Jae Myung Kim, A. Sophia Koepke, et al.. (2023). Waffling around for Performance: Visual Classification with Random Words and Broad Concepts. 15700–15711. 16 indexed citations
6.
Roth, Karsten, Latha Pemula, Joaquin Zepeda, et al.. (2022). Towards Total Recall in Industrial Anomaly Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14298–14308. 622 indexed citations breakdown →
7.
Sinha, Samarth, Karsten Roth, Anirudh Goyal, et al.. (2022). Uniform Priors for Data-Efficient Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 4016–4027. 1 indexed citations
8.
Roth, Karsten, et al.. (2020). Diffuse domain method for needle insertion simulations. International Journal for Numerical Methods in Biomedical Engineering. 36(9). e3377–e3377. 3 indexed citations
9.
Roth, Karsten, et al.. (2020). Sharing Matters for Generalization in Deep Metric Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(1). 416–427. 15 indexed citations
10.
Roth, Karsten, et al.. (2020). Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. 1. 8242–8252. 15 indexed citations
11.
Roth, Karsten, Jürgen Hesser, & Tomasz Konopczyński. (2019). Boosting Liver and Lesion Segmentation from CT Scans By Mask Mining.. arXiv (Cornell University). 1 indexed citations
12.
Brattoli, Biagio, Karsten Roth, & Björn Ommer. (2019). MIC: Mining Interclass Characteristics for Improved Metric Learning. 7999–8008. 45 indexed citations
13.
Roth, Karsten, et al.. (2019). Pharmacokinetics, pharmacodynamics, safety, and immunogenicity of Pelmeg, a pegfilgrastim biosimilar in healthy subjects. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
14.
Wessels, Hendrik, et al.. (2019). Pharmacodynamics, safety, and immunogenicity of Pelmeg®, a pegfilgrastim biosimilar in healthy subjects. Pharmacology Research & Perspectives. 7(5). e00507–e00507. 3 indexed citations
15.
Ritter, Caroline, J. Jansén, Karsten Roth, et al.. (2016). Dairy farmers’ perceptions toward the implementation of on-farm Johne’s disease prevention and control strategies. Journal of Dairy Science. 99(11). 9114–9125. 40 indexed citations
16.
17.
Roth, Karsten, et al.. (1973). [131-I-transferrin in low-protein fed patients with advanced, chronic kidney failure].. PubMed. 79. 719–21. 1 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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