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.
A survey on biometric cryptosystems and cancelable biometrics
2011442 citationsChristian Rathgeb, Andreas Uhlprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Andreas Uhl'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 Andreas Uhl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Uhl more than expected).
This network shows the impact of papers produced by Andreas Uhl. 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 Andreas Uhl. The network helps show where Andreas Uhl may publish in the future.
Co-authorship network of co-authors of Andreas Uhl
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Uhl.
A scholar is included among the top collaborators of Andreas Uhl 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 Andreas Uhl. Andreas Uhl is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Uhl, Andreas, et al.. (2020). Improved Liveness Detection in Dorsal Hand Vein Videos using Photoplethysmography. 9210996.3 indexed citations
9.
Scherhag, Ulrich, Luca Debiasi, Christian Rathgeb, Christoph Busch, & Andreas Uhl. (2019). Detection of Face Morphing Attacks Based on PRNU Analysis. IEEE Transactions on Biometrics Behavior and Identity Science. 1(4). 302–317.67 indexed citations
10.
Prommegger, Bernhard & Andreas Uhl. (2019). Perspective Multiplication for Multi-Perspective Enrolment in Finger Vein Recognition. 107–117.6 indexed citations
11.
Kwitt, Roland, et al.. (2017). Deep Learning with Topological Signatures. Neural Information Processing Systems. 30. 1635–1645.15 indexed citations
Kauba, Christof, et al.. (2014). Pre-processing cascades and fusion in finger vein recognition. 1–6.40 indexed citations
14.
Uhl, Andreas & Peter Wild. (2013). Experimental evidence of ageing in hand biometrics. 1–6.12 indexed citations
15.
Hämmerle-Uhl, Jutta, et al.. (2012). Recognition impact of JPEG2000 Part 2 wavelet packet subband structures in polar iris image compression. International Conference on Systems, Signals and Image Processing. 13–16.1 indexed citations
16.
Maier, Andreas & Andreas Uhl. (2011). Robust automatic indentation localisation and size approximation for Vickers microindentation hardness indentations. 295–300.4 indexed citations
17.
Uhl, Andreas, et al.. (2011). Experiments on improving lossless compression of biometric iris sample data. International Conference on Systems, Signals and Image Processing. 1–4.1 indexed citations
18.
Hegenbart, Sebastian, Andreas Uhl, & Andreas Vécsei. (2011). Impact of endoscopic image degradations on LBP based features using one-class SVM for classification of celiac disease. 715–720.7 indexed citations
19.
Stütz, Thomas & Andreas Uhl. (2010). In)secure multimedia transmission over RTP. European Signal Processing Conference. 2106–2110.1 indexed citations
20.
Uhl, Andreas, et al.. (2009). On JPEG2000 Error Concealment Attacks. Lecture notes in computer science. 5414. 851–861.1 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.