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.
Gradient domain high dynamic range compression
2002825 citationsDani Lischinski, Michael Werman et al.profile →
Gradient domain high dynamic range compression
2002581 citationsDani Lischinski, Michael Werman et al.profile →
Fast and robust Earth Mover's Distances
2009501 citationsOfir Pele, Michael Wermanprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Michael Werman
Since
Specialization
Citations
This map shows the geographic impact of Michael Werman'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 Michael Werman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Werman more than expected).
This network shows the impact of papers produced by Michael Werman. 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 Michael Werman. The network helps show where Michael Werman may publish in the future.
Co-authorship network of co-authors of Michael Werman
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Werman.
A scholar is included among the top collaborators of Michael Werman 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 Michael Werman. Michael Werman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Werman, Michael, et al.. (2023). An Approach to Robust ICP Initialization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(10). 12685–12691.5 indexed citations
Werman, Michael, et al.. (2014). Event Matching from Significantly Different Views using Motion Barcodes.. arXiv (Cornell University).3 indexed citations
6.
Pele, Ofir, Ben Taskar, Amir Globerson, & Michael Werman. (2013). The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification. International Conference on Machine Learning. 205–213.9 indexed citations
7.
Pele, Ofir & Michael Werman. (2009). Fast and robust Earth Mover's Distances. 460–467.501 indexed citations breakdown →
8.
Werman, Michael, et al.. (2006). The World is not always Flat or Learning Curved Manifolds. 58(2). 69–74.5 indexed citations
9.
Werman, Michael, et al.. (2006). Image specific feature similarities.1 indexed citations
Bar‐Joseph, Ziv, Dani Lischinski, Michael Werman, Shlomo Dubnov, & Ran El‐Yaniv. (1999). Granular Synthesis of Sound Textures Using Statistical Learning. The Journal of the Abraham Lincoln Association. 1999.9 indexed citations
14.
Gdalyahu, Yoram, Daphna Weinshall, & Michael Werman. (1998). A Randomized Algorithm for Pairwise Clustering. Neural Information Processing Systems. 11. 424–430.17 indexed citations
15.
Hel-Or, Yacov & Michael Werman. (1994). Constraint-Fusion for Interpretation of Articulated Objects. Computer Vision and Pattern Recognition. 39–45.8 indexed citations
16.
Stein, Andrew N. & Michael Werman. (1992). Finding the repeated median regression line. Symposium on Discrete Algorithms. 409–413.10 indexed citations
Gualtieri, J. Anthony, et al.. (1989). The visual potential: One convex polygon. Computer Vision Graphics and Image Processing. 46(1). 96–130.15 indexed citations
19.
Werman, Michael & Bezalel Peleg. (1988). Gray level requantization. Computer Vision Graphics and Image Processing. 43(1). 81–87.1 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.