Uwe Zscherpel

1.2k total citations · 1 hit paper
56 papers, 782 citations indexed

About

Uwe Zscherpel is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Mechanical Engineering. According to data from OpenAlex, Uwe Zscherpel has authored 56 papers receiving a total of 782 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Biomedical Engineering, 22 papers in Radiology, Nuclear Medicine and Imaging and 18 papers in Mechanical Engineering. Recurrent topics in Uwe Zscherpel's work include Advanced X-ray and CT Imaging (32 papers), Medical Imaging Techniques and Applications (17 papers) and Welding Techniques and Residual Stresses (15 papers). Uwe Zscherpel is often cited by papers focused on Advanced X-ray and CT Imaging (32 papers), Medical Imaging Techniques and Applications (17 papers) and Welding Techniques and Residual Stresses (15 papers). Uwe Zscherpel collaborates with scholars based in Germany, United Kingdom and China. Uwe Zscherpel's co-authors include Uwe Ewert, Hans Löbel, Miguel Carrasco, Vladimir Riffo, Domingo Mery, Iván Lillo, Petra Perner, Kurt Osterloh, B. Staudte and Dietmar Meinel and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Uwe Zscherpel

52 papers receiving 710 citations

Hit Papers

GDXray: The Database of X... 2015 2026 2018 2022 2015 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Uwe Zscherpel Germany 13 307 298 179 154 134 56 782
Wenjuan Sun United Kingdom 16 395 1.3× 236 0.8× 132 0.7× 125 0.8× 64 0.5× 59 771
Clément Jailin France 12 110 0.4× 111 0.4× 144 0.8× 84 0.5× 29 0.2× 31 475
Kazuyuki Demachi Japan 14 152 0.5× 144 0.5× 64 0.4× 45 0.3× 34 0.3× 77 653
Janez Diaci Slovenia 18 331 1.1× 133 0.4× 73 0.4× 135 0.9× 70 0.5× 67 954
André Voet Belgium 8 169 0.6× 226 0.8× 92 0.5× 129 0.8× 39 0.3× 9 511
Oliver Wirjadi Germany 15 80 0.3× 188 0.6× 117 0.7× 128 0.8× 33 0.2× 28 598
Amir Movafeghi Iran 11 150 0.5× 118 0.4× 58 0.3× 43 0.3× 49 0.4× 67 420
Valérie Kaftandjian France 12 103 0.3× 271 0.9× 27 0.2× 212 1.4× 39 0.3× 52 507
Frank Welkenhuyzen Belgium 10 176 0.6× 289 1.0× 43 0.2× 166 1.1× 40 0.3× 22 526
Yudan Wang China 11 56 0.2× 82 0.3× 128 0.7× 35 0.2× 241 1.8× 37 561

Countries citing papers authored by Uwe Zscherpel

Since Specialization
Citations

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

Fields of papers citing papers by Uwe Zscherpel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Uwe Zscherpel

This figure shows the co-authorship network connecting the top 25 collaborators of Uwe Zscherpel. A scholar is included among the top collaborators of Uwe Zscherpel 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 Uwe Zscherpel. Uwe Zscherpel 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
1.
Wang, Xiaopeng, Uwe Zscherpel, Paolo Tripicchio, et al.. (2025). A comprehensive review of welding defect recognition from X-ray images. Journal of Manufacturing Processes. 140. 161–180. 11 indexed citations
2.
Wang, Xiaopeng, Salvatore D’Avella, Baoxin Zhang, et al.. (2025). On the effect of the attention mechanism for automatic welding defects detection based on deep learning. Expert Systems with Applications. 268. 126386–126386. 15 indexed citations
4.
Lopes, Ricardo Tadeu, et al.. (2021). X-ray imaging techniques for inspection of composite pipelines. Micron. 145. 103033–103033. 19 indexed citations
5.
Zscherpel, Uwe, et al.. (2021). Analysis of angular dependent spatial frequency response of Digital Coplanar Translational Laminography. NDT & E International. 124. 102546–102546. 3 indexed citations
6.
Huthwaite, Peter, et al.. (2019). Realistic Film Noise Generation Based on Experimental Noise Spectra. IEEE Transactions on Image Processing. 29. 2987–2998. 3 indexed citations
7.
Ou, Ding Rong, Dominik Schumacher, Uwe Zscherpel, & Yongshun Xiao. (2019). Dual-energy materials characterization methods for laminography image enhancement based on photon counting detector. Journal of Instrumentation. 14(2). P02018–P02018. 3 indexed citations
8.
Ewert, Uwe, et al.. (2018). Visibility of Image Quality Indicators (IQI) by Human Observers in Digital Radiography in Dependence on Measured MTFs and Noise Power Spectra. 2 indexed citations
9.
Ewert, Uwe, et al.. (2017). Influencing parameters on image quality using photon counting detectors for laminography. 3 indexed citations
10.
Zscherpel, Uwe, et al.. (2013). New requirements for digital radiographic testing of welds according to ISO standards. AIP conference proceedings. 1112–1119. 1 indexed citations
11.
Ewert, Uwe, et al.. (2012). Image Quality in Digital Industrial Radiography. Materials Evaluation. 70(8). 8 indexed citations
12.
Ewert, Uwe, et al.. (2012). Best Energy Selection for Different Applications with Digital Detector Arrays from 20 to 600 keV. Materials Evaluation. 70(8). 1 indexed citations
13.
Ewert, Uwe, et al.. (2012). New Measurement Methods of Focal Spot Size and Shape of X-ray Tubes in Digital Radiological Applications in Comparison to Current Standards. 4 indexed citations
14.
Osterloh, Kurt, et al.. (2011). Radiography and partial tomography of wood with thermal neutrons. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 651(1). 236–239. 3 indexed citations
15.
Ewert, Uwe, et al.. (2009). New Compensation Principles for Enhanced Image Quality in Industrial Radiology with Digital Detector Arrays. Materials Evaluation. 68(2). 163–168. 11 indexed citations
16.
Zscherpel, Uwe, et al.. (2007). The EN584 standard for the classification of industrial radiography films and its use in radiographic modelling. 347–352. 2 indexed citations
17.
Perner, Petra & Uwe Zscherpel. (2002). . Engineering Applications of Artificial Intelligence. 15(2). 121–121. 1 indexed citations
18.
Perner, Petra, et al.. (2001). A comparison between neural networks and decision trees based on data from industrial radiographic testing. Pattern Recognition Letters. 22(1). 47–54. 54 indexed citations
19.
Jacobsen, Carsten Suhr & Uwe Zscherpel. (1998). Rißdetektion in Schweißnahtradiographien / Crack Detection in Radiographs of Welds Using Neuronal Networks. Materials Testing. 40(9). 335–341.
20.
Löffler, E., Uwe Zscherpel, Ch. Peuker, & B. Staudte. (1993). IR spectroscopic study of hydroxyl groups of molecular sieves in the fundamental and combination tone regions. Journal of Molecular Structure. 293. 269–272. 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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