Mehrnoosh Sameki

507 total citations
14 papers, 263 citations indexed

About

Mehrnoosh Sameki is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science Applications. According to data from OpenAlex, Mehrnoosh Sameki has authored 14 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Science Applications. Recurrent topics in Mehrnoosh Sameki's work include Mobile Crowdsensing and Crowdsourcing (5 papers), Visual Attention and Saliency Detection (3 papers) and Cell Image Analysis Techniques (3 papers). Mehrnoosh Sameki is often cited by papers focused on Mobile Crowdsensing and Crowdsourcing (5 papers), Visual Attention and Saliency Detection (3 papers) and Cell Image Analysis Techniques (3 papers). Mehrnoosh Sameki collaborates with scholars based in United States, Iran and United Kingdom. Mehrnoosh Sameki's co-authors include Margrit Betke, Hanna Wallach, R. J. Edgar, Kathleen Walker, Sarah Bird, Brandon Horn, Danna Gurari, Stan Sclaroff, Brian Price and Xiaohui Shen and has published in prestigious journals such as International Journal of Computer Vision, International Journal of Human-Computer Interaction and arXiv (Cornell University).

In The Last Decade

Mehrnoosh Sameki

14 papers receiving 257 citations

Peers

Mehrnoosh Sameki
Comparison fields: 5 of 74
  • Artificial Intelligence 126
  • Computer Vision and Pattern Recognition 81
  • Safety Research 69
  • Computer Science Applications 39
  • Health Informatics 24
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Citations per field, relative to Mehrnoosh Sameki
Mehrnoosh Sameki · 1×
Citations per year, relative to Mehrnoosh Sameki
Mehrnoosh Sameki · 1×

Countries citing papers authored by Mehrnoosh Sameki

Since Specialization
Citations

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

Fields of papers citing papers by Mehrnoosh Sameki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehrnoosh Sameki

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

All Works

14 of 14 papers shown
# Work Indexed citations
1 7
2 4
3
Fairlearn: A toolkit for assessing and improving fairness in AI
112
4
Assessing and mitigating unfairness in credit models with the Fairlearn toolkit
4
5 5
6 3
7 11
8 9
9 5
10 3
11 42
12 54
13 3
14 1

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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