Erik Rodner

3.8k total citations
52 papers, 1.5k citations indexed

About

Erik Rodner is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Erik Rodner has authored 52 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 6 papers in Media Technology. Recurrent topics in Erik Rodner's work include Domain Adaptation and Few-Shot Learning (11 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Anomaly Detection Techniques and Applications (10 papers). Erik Rodner is often cited by papers focused on Domain Adaptation and Few-Shot Learning (11 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Anomaly Detection Techniques and Applications (10 papers). Erik Rodner collaborates with scholars based in Germany, United States and Netherlands. Erik Rodner's co-authors include Joachim Denzler, Marcel Simon, Kate Saenko, Judy Hoffman, Jeff Donahue, Trevor Darrell, Alexander Freytag, Michael Kemmler, Paul Bodesheim and Andreas Maier and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Analytica Chimica Acta.

In The Last Decade

Erik Rodner

51 papers receiving 1.5k citations

Peers

Erik Rodner

CVPR

RNMI

Ashnil Kumar Australia

Ahmet Çınar Türkiye

Wei Huang China

Bo Zhao China

Marina Skurichina Netherlands

Idit Diamant Israel

Mesut Toğaçar Türkiye

Şaban Öztürk Türkiye

Houjin Chen China

Domenico D. Bloisi Italy

Ashnil Kumar Australia

Erik Rodner

875 ×1.0

712 ×1.0

CVPR

499 ×2.8

RNMI

168 ×1.6

114 ×1.3

Citations per year, relative to Erik Rodner Erik Rodner (= 1×) peers Ashnil Kumar

Countries citing papers authored by Erik Rodner

Since Specialization

Citations

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

Fields of papers citing papers by Erik Rodner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Erik Rodner

This figure shows the co-authorship network connecting the top 25 collaborators of Erik Rodner. A scholar is included among the top collaborators of Erik Rodner 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 Erik Rodner. Erik Rodner 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

Reiß, Simon, Constantin Seibold, Alexander Freytag, Erik Rodner, & Rainer Stiefelhagen. (2023). Decoupled Semantic Prototypes enable learning from diverse annotation types for semi-weakly segmentation in expert-driven domains. 15495–15506. 4 indexed citations

Seibold, Constantin, et al.. (2021). Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation. 9527–9537. 52 indexed citations

Käding, Christoph, et al.. (2018). Active Learning for Regression Tasks with Expected Model Output Changes.. British Machine Vision Conference. 103. 8 indexed citations

Flach, Milan, Fabian Gans, Alexander Brenning, et al.. (2017). Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques. Earth System Dynamics. 8(3). 677–696. 32 indexed citations

Aubreville, Marc, Christian Knipfer, Nicolai Oetter, et al.. (2017). Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning. Scientific Reports. 7(1). 11979–11979. 214 indexed citations

Rodner, Erik, Marcel Simon, & Joachim Denzler. (2017). Deep bilinear features for Her2 scoring in digital pathology. Current Directions in Biomedical Engineering. 3(2). 811–814. 6 indexed citations

Käding, Christoph, Erik Rodner, Alexander Freytag, & Joachim Denzler. (2016). Watch, Ask, Learn, and Improve: a lifelong learning cycle for visual recognition.. The European Symposium on Artificial Neural Networks. 4 indexed citations

Reichstein, Markus, Martin Jung, Paul Bodesheim, et al.. (2016). Potential of new machine learning methods for understanding long-term interannual variability of carbon and energy fluxes and states from site to global scale. AGU Fall Meeting Abstracts. 2016. 1 indexed citations

Rodner, Erik, et al.. (2016). SeaCLEF 2016: Object Proposal Classification for Fish Detection in Underwater Videos.. CLEF (Working Notes). 481–489. 26 indexed citations

10.

Sickert, Sven, Erik Rodner, & Joachim Denzler. (2016). Semantic volume segmentation with iterative context integration for bio-medical image stacks. Pattern Recognition and Image Analysis. 26(1). 197–204. 2 indexed citations

11.

Rodner, Erik, et al.. (2016). Large-Scale Gaussian Process Inference with Generalized Histogram Intersection Kernels for Visual Recognition Tasks. International Journal of Computer Vision. 121(2). 253–280. 4 indexed citations

12.

Darrell, Trevor, Marius Kloft, Massimiliano Pontil, Gunnar Rätsch, & Erik Rodner. (2015). Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 6 indexed citations

13.

Rodner, Erik, et al.. (2014). Bildverarbeitung und Objekterkennung. 3 indexed citations

14.

Kemmler, Michael, Erik Rodner, Petra Rösch, Jürgen Popp, & Joachim Denzler. (2013). Automatic identification of novel bacteria using Raman spectroscopy and Gaussian processes. Analytica Chimica Acta. 794. 29–37. 18 indexed citations

15.

Kemmler, Michael, et al.. (2013). One-class classification with Gaussian processes. Pattern Recognition. 46(12). 3507–3518. 88 indexed citations

16.

Rodner, Erik, et al.. (2013). Large-scale gaussian process multi-class classification for semantic segmentation and facade recognition. Machine Vision and Applications. 24(5). 1043–1053. 11 indexed citations

17.

Rodner, Erik, et al.. (2010). Multiple kernel Gaussian process classification for generic 3D object recognition. 1–8. 6 indexed citations

18.

Rodner, Erik & Joachim Denzler. (2010). Learning with few examples for binary and multiclass classification using regularization of randomized trees. Pattern Recognition Letters. 32(2). 244–251. 8 indexed citations

19.

Rodner, Erik & Joachim Denzler. (2008). Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees.. Vision Modeling and Visualization. 159–168. 3 indexed citations

20.

Rodner, Erik, et al.. (2008). Difference of Boxes Filters Revisited: Shadow Suppression and Efficient Character Segmentation. 263–269. 7 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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