Maryam Fatemi

17 papers receiving 376 citations

Peers

Maryam Fatemi
Comparison fields: 5 of 45
  • Artificial Intelligence 270
  • Aerospace Engineering 141
  • Automotive Engineering 71
  • Computer Vision and Pattern Recognition 69
  • Computer Networks and Communications 59
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Ting Yuan China
Gongjian Zhou China
Tzvetan Semerdjiev Bulgaria
John Mullane Singapore
Marcus Obst Germany
Isaac Miller United States
Xiwei Bai Hong Kong
Denis Pomorski France
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Ju Hong Yoon South Korea
Maryam Fatemi relative to Ting Yuan China Ting Yuan's profile →
Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Maryam Fatemi

Since Specialization
Citations

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

Fields of papers citing papers by Maryam Fatemi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maryam Fatemi

This figure shows the co-authorship network connecting the top 25 collaborators of Maryam Fatemi. A scholar is included among the top collaborators of Maryam Fatemi 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 Maryam Fatemi. Maryam Fatemi 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 2
2 0
3 3
4 32
5 119
6 4
7 50
8
Extended Target Poisson Multi-Bernoulli Filter
3
9 34
10 38
11
Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter for extended target tracking
34
12 21
13
Poisson Multi-Bernoulli Radar Mapping Using Gibbs Sampling
1
14 6
15 11
16 28
17
A study of MAP estimation techniques for nonlinear filtering
11
18 2

About Maryam Fatemi

Maryam Fatemi is a scholar working on Automotive Engineering, Artificial Intelligence and Instrumentation, having authored 18 papers that have together received 399 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (13 papers), Autonomous Vehicle Technology and Safety (6 papers) and Gaussian Processes and Bayesian Inference (4 papers). The work is most often cited by research in Artificial Intelligence (270 citations), Automotive Engineering (71 citations) and Aerospace Engineering (141 citations). Maryam Fatemi has collaborated with scholars based in Sweden, Australia and Germany. Frequent co-authors include Lennart Svensson, Karl Granström, Lars Hammarstrand, Ángel F. García‐Fernández, Yuxuan Xia, Stephan Reuter, Francisco J. R. Ruiz, Jason Williams, Mark R. Morelande and Mohammad Reza Daliri. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Aerospace and Electronic Systems.

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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