Arsalane Zarghili
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Signal Processing top 10%
- Human-Computer Interaction top 10%
- Cognitive Neuroscience
- Co-authors
- Aicha MajdaKhalid ZenkouarNajia Es-SbaiHakim El FadiliRachid AalouaneVito PirrelliDjamal MeradRachid Benslimane
- Topics
- Face and Expression Recognition (11 papers)Image Retrieval and Classification Techniques (10 papers)Speech and Audio Processing (8 papers)
In The Last Decade
Arsalane Zarghili
45 papers receiving 260 citations
Peers
Comparison fields: 5 of 93
- Computer Vision and Pattern Recognition 147
- Artificial Intelligence 65
- Signal Processing 54
- Human-Computer Interaction 28
- Cognitive Neuroscience 26
Countries citing papers authored by Arsalane Zarghili
This map shows the geographic impact of Arsalane Zarghili'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 Arsalane Zarghili with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arsalane Zarghili more than expected).
Fields of papers citing papers by Arsalane Zarghili
This network shows the impact of papers produced by Arsalane Zarghili. 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 Arsalane Zarghili. The network helps show where Arsalane Zarghili may publish in the future.
Co-authorship network of co-authors of Arsalane Zarghili
This figure shows the co-authorship network connecting the top 25 collaborators of Arsalane Zarghili. A scholar is included among the top collaborators of Arsalane Zarghili 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 Arsalane Zarghili. Arsalane Zarghili is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 19 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 40 | |
| 10 | 1 | |
| 11 | Al Qamus al Muhit: a medieval Arabic lexicon in LMF | 2 |
| 12 | 2 | |
| 13 | 5 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 13 | |
| 19 | 1 | |
| 20 | 4 |
About Arsalane Zarghili
Arsalane Zarghili is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Signal Processing, having authored 48 papers that have together received 273 indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Image Retrieval and Classification Techniques (10 papers) and Speech and Audio Processing (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (147 citations), Human-Computer Interaction (28 citations) and Signal Processing (54 citations). Arsalane Zarghili has collaborated with scholars based in Morocco, France and Italy. Frequent co-authors include Aicha Majda, Khalid Zenkouar, Najia Es-Sbai, Hakim El Fadili, Rachid Aalouane, Vito Pirrelli, Djamal Merad, Rachid Benslimane, Hassan Qjidaa and Kadi Bouatouch. Their work appears in journals such as IEEE Access, Pattern Recognition Letters and Multimedia Tools and Applications.
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.