Shai Bagon

52 total papers · 3.4k total citations
17 papers, 1.8k citations indexed

About

Shai Bagon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shai Bagon has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shai Bagon's work include Generative Adversarial Networks and Image Synthesis (5 papers), Advanced Image Processing Techniques (5 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Shai Bagon is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (5 papers), Advanced Image Processing Techniques (5 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Shai Bagon collaborates with scholars based in Israel, United States and Italy. Shai Bagon's co-authors include Michal Irani, Daniel Gläsner, Narek Tumanyan, Tali Dekel, Michal Geyer, Assaf Shocher, Phillip Isola, Omer Bar-Tal, Sebastian Nowozin and Pushmeet Kohli and has published in prestigious journals such as Nature Communications, Nature Biotechnology and The Journal of the Acoustical Society of America.

In The Last Decade

Shai Bagon

16 papers receiving 1.8k citations

Hit Papers

Super-resolution from a s... 2009 2026 2014 2020 2009 2023 400 800 1.2k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shai Bagon 1.6k 745 127 120 100 17 1.8k
Egon Pasztor 2.0k 1.2× 1.0k 1.4× 82 0.6× 190 1.6× 68 0.7× 6 2.1k
Ardeshir Goshtasby 1.2k 0.8× 303 0.4× 94 0.7× 158 1.3× 94 0.9× 34 1.8k
Jinjin Gu 1.4k 0.9× 476 0.6× 99 0.8× 66 0.6× 191 1.9× 32 1.7k
Xiaodong Cun 1.8k 1.2× 585 0.8× 102 0.8× 72 0.6× 196 2.0× 37 2.2k
Zhendong Wang 1.1k 0.7× 502 0.7× 117 0.9× 183 1.5× 114 1.1× 44 1.8k
Daniel Gläsner 1.6k 1.0× 849 1.1× 34 0.3× 87 0.7× 168 1.7× 17 1.8k
Greg Shakhnarovich 1.4k 0.9× 729 1.0× 105 0.8× 118 1.0× 46 0.5× 19 1.6k
M.J. Black 1.5k 1.0× 413 0.6× 86 0.7× 186 1.6× 193 1.9× 16 1.8k
Stephen T. Barnard 1.5k 0.9× 265 0.4× 167 1.3× 120 1.0× 112 1.1× 21 2.1k
Daniel Zoran 1.3k 0.8× 749 1.0× 44 0.3× 236 2.0× 144 1.4× 18 1.5k

Countries citing papers authored by Shai Bagon

Since Specialization
Citations

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

Fields of papers citing papers by Shai Bagon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shai Bagon

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

All Works

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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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