Saïd Safi

758 citations
98 papers · 485 · h-index 10

Impact in

Papers in

Saïd Safi

82 papers receiving 430 citations

Peers

Saïd Safi
Comparison fields: 5 of 100
  • Signal Processing 166
  • Artificial Intelligence 124
  • Modeling and Simulation 14
  • Computational Mechanics 61
  • Computer Networks and Communications 67
Replace Samer Atawneh with:
Samer Atawneh Saudi Arabia
Hongjian Wang United States
Cheng Yang China
Dian Liu China
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Saïd Safi relative to Samer Atawneh Saudi Arabia Samer Atawneh's profile →
Citations per field
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Citations per year

Countries citing papers authored by Saïd Safi

Since Specialization
Citations

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

Fields of papers citing papers by Saïd Safi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Saïd Safi, 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 Saïd Safi Line = papers co-authored together Saïd Safi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202086
2 200256
3 201438
4 201815
5 200315
6 201113
7 202113
8 201012
9 201812
10 200210
11 20159
12 20089
13 20237
14 20177
15 20147
16 20216
17
Printed Eastern Arabic Noisy Numerals Recognition Using Hidden Markov Model and Support Vectors Machine
20146
18 20146
19 20176
20 20155

About Saïd Safi

Saïd Safi is a scholar working on Signal Processing, Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 98 papers that have together received 485 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (37 papers), Advanced Wireless Communication Techniques (18 papers), Control Systems and Identification (17 papers), Wireless Communication Networks Research (16 papers), Advanced Adaptive Filtering Techniques (14 papers), Speech and Audio Processing (14 papers), Handwritten Text Recognition Techniques (8 papers) and Neural Networks and Applications (8 papers). The work is most often cited by research in Signal Processing (166 citations), Artificial Intelligence (124 citations), Modeling and Simulation (14 citations), Computational Mechanics (61 citations) and Computer Networks and Communications (67 citations). Saïd Safi has collaborated with scholars based in Morocco, France and Portugal. Frequent co-authors include Belaid Bouikhalene, Abdelouhab Zeroual, Moha M’Rabet Hassani, B. Manaut, Mohamed Fakir, Mohammed M’Saad, Samira Chabaa, M. M’Saad, Mohamed Baslam and Estelle Cherrier. Their work appears in journals such as International Journal of Speech Technology, Journal of Statistical Computation and Simulation, Applied Computing and Informatics, Data in Brief and Renewable Energy.

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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