Klaus Diepold

3.7k total citations · 1 hit paper
182 papers, 2.3k citations indexed

About

Klaus Diepold is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Klaus Diepold has authored 182 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Computer Vision and Pattern Recognition, 45 papers in Signal Processing and 45 papers in Artificial Intelligence. Recurrent topics in Klaus Diepold's work include Image and Video Quality Assessment (30 papers), Speech and Audio Processing (27 papers) and Advanced Vision and Imaging (22 papers). Klaus Diepold is often cited by papers focused on Image and Video Quality Assessment (30 papers), Speech and Audio Processing (27 papers) and Advanced Vision and Imaging (22 papers). Klaus Diepold collaborates with scholars based in Germany, Lebanon and Egypt. Klaus Diepold's co-authors include Sven Gronauer, Christian Keimel, Julian Habigt, Johannes Günther, Patrick M. Pilarski, Hao Shen, Fakheredine Keyrouz, Tobias Oelbaum, Michel Sarkis and Simon Hawe and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Image Processing.

In The Last Decade

Klaus Diepold

160 papers receiving 2.1k citations

Hit Papers

Multi-agent deep reinforcement learning: a survey 2021 2026 2022 2024 2021 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Klaus Diepold Germany 20 914 427 353 243 235 182 2.3k
M. Hassaballah Egypt 27 1.2k 1.3× 911 2.1× 271 0.8× 218 0.9× 94 0.4× 84 2.8k
Yimin Yang China 30 870 1.0× 1.0k 2.5× 182 0.5× 458 1.9× 414 1.8× 149 3.1k
Fabio Scotti Italy 30 1.8k 1.9× 915 2.1× 1.1k 3.2× 194 0.8× 145 0.6× 161 3.5k
Fei Wu China 29 1.9k 2.1× 972 2.3× 178 0.5× 187 0.8× 214 0.9× 188 4.2k
Jürgen Beyerer Germany 27 1.9k 2.1× 517 1.2× 105 0.3× 240 1.0× 367 1.6× 420 3.5k
Sonya Coleman United Kingdom 22 999 1.1× 410 1.0× 88 0.2× 333 1.4× 129 0.5× 240 2.6k
Alberto Sanfeliu Spain 33 2.7k 3.0× 1.0k 2.4× 314 0.9× 266 1.1× 169 0.7× 200 4.1k
Gang Chen China 23 639 0.7× 285 0.7× 138 0.4× 242 1.0× 513 2.2× 340 2.4k
Daijin Kim South Korea 34 2.9k 3.1× 1.0k 2.4× 473 1.3× 348 1.4× 90 0.4× 179 4.2k

Countries citing papers authored by Klaus Diepold

Since Specialization
Citations

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

Fields of papers citing papers by Klaus Diepold

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Klaus Diepold

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

All Works

20 of 20 papers shown
2.
Diepold, Klaus, et al.. (2023). Measurement of Platelet Aggregation in Ageing Samples and After in-Vitro Activation. mediaTUM (Technical University of Munich). 57–65. 1 indexed citations
4.
Erber, Johanna, Martin Schlegel, Bernhard Haller, et al.. (2023). Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity. SHILAP Revista de lepidopterología. 3(1). 161–161. 13 indexed citations
5.
Günther, Johannes, et al.. (2020). Interpretable PID parameter tuning for control engineering using general dynamic neural networks: An extensive comparison. PLoS ONE. 15(12). e0243320–e0243320. 13 indexed citations
6.
Diepold, Klaus, et al.. (2012). DELIMITING STRUCTURAL AND DYNAMICAL SYSTEM ANALYSIS IN ENGINEERING MANAGEMENT. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1649–1656. 2 indexed citations
7.
Shen, Hao, et al.. (2012). L1 Regularized Gradient Temporal-Difference Learning. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1 indexed citations
8.
Keimel, Christian, Julian Habigt, & Klaus Diepold. (2012). Hybrid no-reference video quality metric based on multiway PLSR. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1244–1248. 8 indexed citations
9.
Keimel, Christian, et al.. (2011). Video is a Cube: Multidimensional Analysis and Video Quality Metrics. IEEE Signal Processing Magazine. 41–49. 3 indexed citations
10.
Zwick, Michael E., et al.. (2010). Predicting Cache Contention with Setvectors. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 2 indexed citations
11.
Diepold, Klaus, et al.. (2010). Structural Complexity Management using domain-spanning structural criteria. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 827–834. 2 indexed citations
12.
Diepold, Klaus, et al.. (2010). HRTF Measurements with Recorded Reference Signal. Journal of the Audio Engineering Society. 1 indexed citations
13.
Diepold, Klaus, et al.. (2010). COMBINING STRUCTURAL COMPLEXITY MANAGEMENT AND HYBRID DYNAMICAL SYSTEM MODELLING. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1045–1054. 6 indexed citations
14.
Shen, Hao, et al.. (2010). HRTF customization using multiway array analysis. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 229–233. 9 indexed citations
15.
Hawe, Simon, et al.. (2009). MutanT: A modular and generic tool for multi-sensor data processing. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 1304–1309. 2 indexed citations
16.
Diepold, Klaus, et al.. (2009). A cognitive approach for a robotic welding system learning how to weld from acoustic data.
17.
Sarkis, Michel & Klaus Diepold. (2008). Towards Real-time Stereo using Non-uniform Image Sampling and Sparse Dynamic Programming. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 3 indexed citations
18.
Keyrouz, Fakheredine & Klaus Diepold. (2008). A New HRTF Interpolation Approach for Fast Synthesis of Dynamic Environmental Interaction. Journal of the Audio Engineering Society. 56. 28–35. 14 indexed citations
19.
Oelbaum, Tobias & Klaus Diepold. (2008). Building a Reduced Reference Video Quality Metric with Very Low Overhead Using Multivariate Data Analysis. SHILAP Revista de lepidopterología. 3 indexed citations
20.
Oelbaum, Tobias, et al.. (2007). A generic method to increase the prediction accuracy of visual quality metrics. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 14 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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