Shai Har-El

2.3k citations
18 papers · 1.4k indexed · 1 hit paper · h-index 12
Topics
Face recognition and analysis (4 papers)Entrepreneurship Studies and Influences (3 papers)Face and Expression Recognition (3 papers)

In The Last Decade

Shai Har-El

17 papers receiving 1.3k citations

Hit Papers

Effective face frontalization in unconstrained images20152026201820222015100200300

Peers

Shai Har-El
Comparison fields: 5 of 122
  • Computer Vision and Pattern Recognition 558
  • Pulmonary and Respiratory Medicine 283
  • Nephrology 280
  • Signal Processing 250
  • Cardiology and Cardiovascular Medicine 223
Replace Benjamin Shickel with:
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Yoshihiro Noguchi Japan
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Shai Har-El relative to Benjamin Shickel United States Benjamin Shickel's profile →
Citations per field
00.5×10×20×29.8×
Benjamin Shickel · 1×
Citations per year

Countries citing papers authored by Shai Har-El

Since Specialization
Citations

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

Fields of papers citing papers by Shai Har-El

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shai Har-El. 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 Shai Har-El. The network helps show where Shai Har-El may publish in the future.

Co-authorship network of co-authors of Shai Har-El

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 10
2 9
3 118
4 66
5 54
6 23
7 40
8 1
9 92
10 4
11 133
12 64
13
Effective face frontalization in unconstrained imagesbreakdown →
389
14 84
15 39
16
Where Islam and Judaism Join Together: A Perspective on Reconciliation
0
17 232
18 10

About Shai Har-El

Shai Har-El is a scholar working on Nephrology, Management of Technology and Innovation and Accounting, having authored 18 papers that have together received 1.4k indexed citations. Recurring topics across this work include Face recognition and analysis (4 papers), Entrepreneurship Studies and Influences (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Nephrology (280 citations), Computer Vision and Pattern Recognition (558 citations) and Signal Processing (250 citations). Shai Har-El has collaborated with scholars based in Canada, Israel and United States. Frequent co-authors include Tal Hassner, Ziv Harel, Ron Wald, Prakesh S. Shah, Chaim M. Bell, Jeffrey Perl, Samuel A. Silver, Glenn M. Chertow, Iacopo Masi and Prem Natarajan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Research Policy and The American Journal of Medicine.

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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