Abbas Sadat

713 citations
5 papers · 411 indexed · h-index 4
Topics
Autonomous Vehicle Technology and Safety (5 papers)Advanced Neural Network Applications (3 papers)Human Pose and Action Recognition (2 papers)
Journals
2021 IEEE/CVF International Conference on Computer Vision (ICCV)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Partner nations
CanadaUnited States

In The Last Decade

Abbas Sadat

5 papers receiving 386 citations

Peers

Abbas Sadat
Comparison fields: 5 of 41
  • Automotive Engineering 303
  • Computer Vision and Pattern Recognition 203
  • Artificial Intelligence 149
  • Control and Systems Engineering 81
  • Safety, Risk, Reliability and Quality 47
Replace Maximilian Naumann with:
Maximilian Naumann Germany
Andreas Tamke Germany
Jarrod Snider United States
Marc René Zofka Germany
Tobias Moers Germany
Ömer Şahin Taş Germany
Fabian Poggenhans Germany
Maria Chiara Laghi Italy
Antonio Prioletti Italy
Jiatong Du China
Abbas Sadat relative to Maximilian Naumann Germany Maximilian Naumann's profile →
Citations per field
00.5×3.9×
Maximilian Naumann · 1×
Citations per year

Countries citing papers authored by Abbas Sadat

Since Specialization
Citations

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

Fields of papers citing papers by Abbas Sadat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abbas Sadat

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

All Works

About Abbas Sadat

Abbas Sadat is a scholar working on Automotive Engineering, Software and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 411 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (5 papers), Advanced Neural Network Applications (3 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Automotive Engineering (303 citations), Computer Vision and Pattern Recognition (203 citations) and Safety, Risk, Reliability and Quality (47 citations). Abbas Sadat has collaborated with scholars based in Canada and United States. Frequent co-authors include Raquel Urtasun, Sergio Casas, Bin Yang, Simon Su, Wenjie Luo, Wenyuan Zeng, Renjie Liao, James Tu, Mengye Ren and Jingkang Wang. Their work appears in journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

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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