Michael Hirsch

56 papers receiving 2.4k citations

Hit Papers

Learning to Deblur 2015 · 376 citations
3762015202620182022100200300

Peers

Michael Hirsch
Comparison fields: 5 of 117
  • Media Technology 651
  • Computer Vision and Pattern Recognition 1.2k
  • Biophysics 125
  • Acoustics and Ultrasonics 19
  • Instrumentation 70
Replace Mikhail A. Belkin with:
Mikhail A. Belkin United States
William T. Rhodes United States
Peter Jansson Sweden
K. Sauer United States
Zhixun Su China
Shigeo Minami Japan
M. Rosenbluh Israel
S. F. Gull United Kingdom
Daomu Zhao China
Lionel Moisan France
Michael Hirsch relative to Mikhail A. Belkin United States Mikhail A. Belkin's profile →
Citations per field
00.5×8.8×
Mikhail A. Belkin · 1×
Citations per year

Countries citing papers authored by Michael Hirsch

Since Specialization
Citations

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

Fields of papers citing papers by Michael Hirsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Hirsch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Hirsch Line = papers co-authored together Michael Hirsch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning to Deblur
Hit paper breakdown →
2015376
2 2011216
3 1998155
4 2010147
5 1998122
6 2017100
7 201794
8
Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake
201082
9 201373
10 200464
11 201163
12 201960
13 201254
14 201752
15 201851
16 199945
17 200443
18 201341
19 200240
20 200240

About Michael Hirsch

Michael Hirsch is a scholar working on Structural Biology, Biophysics, Computer Vision and Pattern Recognition, Media Technology and Physical and Theoretical Chemistry, having authored 57 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (15 papers), Advanced Fluorescence Microscopy Techniques (10 papers), Advanced Vision and Imaging (8 papers), Image and Signal Denoising Methods (8 papers), Advanced Chemical Physics Studies (6 papers), Image Processing Techniques and Applications (5 papers), HER2/EGFR in Cancer Research (5 papers) and Advanced Biosensing Techniques and Applications (5 papers). The work is most often cited by research in Media Technology (651 citations), Computer Vision and Pattern Recognition (1.2k citations), Biophysics (125 citations), Acoustics and Ultrasonics (19 citations) and Instrumentation (70 citations). Michael Hirsch has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Bernhard Schölkopf, Stefan Harmeling, Wolfgang Quapp, Christian J. Schuler, Dietmar Heidrich, Suvrit Sra, Marisa L. Martin-Fernandez, Daniel J. Rolfe, Tae Hyun Kim and Kyoung Mu Lee. Their work appears in journals such as Journal of Computational Chemistry, Theoretical Chemistry Accounts, Monthly Notices of the Royal Astronomical Society, PLoS ONE and Journal of Computational Biology.

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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