Salman Khan

39 total papers · 1.5k total citations
17 papers, 706 citations indexed

About

Salman Khan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surgery. According to data from OpenAlex, Salman Khan has authored 17 papers receiving a total of 706 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Surgery. Recurrent topics in Salman Khan's work include Domain Adaptation and Few-Shot Learning (2 papers), Artificial Intelligence in Healthcare (2 papers) and Multimodal Machine Learning Applications (2 papers). Salman Khan is often cited by papers focused on Domain Adaptation and Few-Shot Learning (2 papers), Artificial Intelligence in Healthcare (2 papers) and Multimodal Machine Learning Applications (2 papers). Salman Khan collaborates with scholars based in United Arab Emirates, United States and Saudi Arabia. Salman Khan's co-authors include Fahad Shahbaz Khan, Syed Waqas Zamir, Fahad Shamshad, Huazhu Fu, Muhammad Haris Khan, Munawar Hayat, Prasun Kumar Gupta, S. Zhou, Gurulingappa Hallur and József Barkóczy and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Computer Vision and Medical Image Analysis.

In The Last Decade

Salman Khan

11 papers receiving 690 citations

Hit Papers

Transformers in medical i... 2023 2026 2024 2023 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Salman Khan 289 238 235 128 95 17 706
Qiang Zheng 206 0.7× 103 0.4× 198 0.8× 159 1.2× 63 0.7× 59 838
Máté E. Maros 260 0.9× 191 0.8× 76 0.3× 153 1.2× 50 0.5× 43 881
Bingtao Zhang 159 0.6× 173 0.7× 217 0.9× 152 1.2× 86 0.9× 27 800
Marı́a J. Carreira 425 1.5× 131 0.6× 226 1.0× 54 0.4× 34 0.4× 39 786
Judith M. S. Prewitt 107 0.4× 126 0.5× 263 1.1× 82 0.6× 10 0.1× 24 859
Boklye Kim 489 1.7× 61 0.3× 362 1.5× 109 0.9× 13 0.1× 26 876
Xin Luo 129 0.4× 168 0.7× 182 0.8× 59 0.5× 59 0.6× 42 776
Bassem Ben Cheikh 293 1.0× 437 1.8× 338 1.4× 44 0.3× 57 0.6× 18 759
Yigang Luo 125 0.4× 68 0.3× 57 0.2× 329 2.6× 33 0.3× 36 885
Loïc Peter 197 0.7× 167 0.7× 215 0.9× 207 1.6× 59 0.6× 20 820

Countries citing papers authored by Salman Khan

Since Specialization
Citations

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

Fields of papers citing papers by Salman Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salman Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Salman Khan. A scholar is included among the top collaborators of Salman Khan 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 Salman Khan. Salman Khan 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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