Nabil Zerrouki

816 citations
32 papers · 561 · h-index 11

Impact in

Papers in

Nabil Zerrouki

30 papers receiving 532 citations

Peers

Nabil Zerrouki
Comparison fields: 5 of 85
  • Computer Vision and Pattern Recognition 334
  • Media Technology 81
  • Human-Computer Interaction 37
  • Biomedical Engineering 198
  • Artificial Intelligence 129
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Shuang Bai China
Albert Dipandà France
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Qi Zou China
Guangle Yao China
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B. S. Sathish India
Wei-Lwun Lu Canada
Cunzhao Shi China
Hernsoo Hahn South Korea
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Citations per field
00.5×6.2×
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Citations per year

Countries citing papers authored by Nabil Zerrouki

Since Specialization
Citations

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

Fields of papers citing papers by Nabil Zerrouki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Nabil Zerrouki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nabil Zerrouki Line = papers co-authored together Nabil Zerrouki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201786
2 201864
3 201962
4 201753
5 201937
6 202037
7 201628
8 201428
9 201625
10 201419
11 201815
12 202210
13 202410
14 20249
15 20169
16 20217
17 20237
18 20227
19 20246
20 20166

About Nabil Zerrouki

Nabil Zerrouki is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Ecology, Media Technology and Artificial Intelligence, having authored 32 papers that have together received 561 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (10 papers), Remote Sensing in Agriculture (9 papers), Remote-Sensing Image Classification (8 papers), Gait Recognition and Analysis (7 papers), Human Pose and Action Recognition (7 papers), Anomaly Detection Techniques and Applications (7 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Hand Gesture Recognition Systems (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (334 citations), Media Technology (81 citations), Human-Computer Interaction (37 citations), Biomedical Engineering (198 citations) and Artificial Intelligence (129 citations). Nabil Zerrouki has collaborated with scholars based in Algeria, Saudi Arabia and Sweden. Frequent co-authors include Amrane Houacine, Fouzi Harrou, Ying Sun, Djamel Bouchaffra, Abdelkader Dairi, Benamar Bouyeddou, A. Aissat, Ahmed Bentaleb, Samir Benbelkacem and Sos С. Agaian. Their work appears in journals such as IEEE Sensors Journal, Measurement, IEEE Geoscience and Remote Sensing Letters, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and IEEE Access.

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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