Ibrahim Ouahbi

490 total citations · 2 hit papers
38 papers, 278 citations indexed

About

Ibrahim Ouahbi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Ibrahim Ouahbi has authored 38 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 7 papers in Human-Computer Interaction. Recurrent topics in Ibrahim Ouahbi's work include Hand Gesture Recognition Systems (7 papers), Teaching and Learning Programming (5 papers) and Handwritten Text Recognition Techniques (4 papers). Ibrahim Ouahbi is often cited by papers focused on Hand Gesture Recognition Systems (7 papers), Teaching and Learning Programming (5 papers) and Handwritten Text Recognition Techniques (4 papers). Ibrahim Ouahbi collaborates with scholars based in Morocco, Saudi Arabia and Bangladesh. Ibrahim Ouahbi's co-authors include Hassane Darhmaoui, Khalid El Makkaoui, Yassine Maleh, Ahmed A. Abd El‐Latif, Paweł Pławiak, Fahad Alblehai, Dusit Niyato, Osama Alfarraj, Jialiang Peng and Ali Abdullah S. AlQahtani and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Access.

In The Last Decade

Ibrahim Ouahbi

33 papers receiving 265 citations

Hit Papers

Tiny Language Models for Automation and Control: Overview... 2025 2026 2025 2025 5 10 15
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions
    2025 18 citations Yassine Maleh, Khalid El Makkaoui et al. Sensors profile →
  2. A Comprehensive Survey on Tiny Machine Learning for Human Behavior Analysis
    2025 18 citations Yassine Maleh, Khalid El Makkaoui et al. IEEE Internet of Things Journal profile →

Peers

Ibrahim Ouahbi
Françeska Xhakaj United States
Jürgen Mottok Germany
Shinobu Hasegawa Japan
Paraskevi Tzouveli Greece
Alenka Kavčič Slovenia
Leônidas de Oliveira Brandão Brazil
Amali Weerasinghe Australia
Anarosa A. F. Brandão Brazil
Aidan Mooney Ireland
Ramkumar Rajendran India
Françeska Xhakaj United States
Ibrahim Ouahbi
Citations per year, relative to Ibrahim Ouahbi Ibrahim Ouahbi (= 1×) peers Françeska Xhakaj

Countries citing papers authored by Ibrahim Ouahbi

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Ouahbi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ibrahim Ouahbi

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

All Works

20 of 20 papers shown
1.
Maleh, Yassine, Khalid El Makkaoui, Ibrahim Ouahbi, et al.. (2025). Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions. Sensors. 25(5). 1318–1318. 18 indexed citations breakdown →
2.
Maleh, Yassine, et al.. (2025). Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions. IEEE Access. 13. 128379–128419. 8 indexed citations
3.
Maleh, Yassine, et al.. (2025). An Explainable Tiny-Fast Kolmogorov–Arnold Network for Gesture-Based Air Handwriting Recognition of Tifinagh Letters in Resource-Constrained IoT Device. IEEE Internet of Things Journal. 12(24). 55756–55773. 3 indexed citations
4.
Maleh, Yassine, Khalid El Makkaoui, Ibrahim Ouahbi, et al.. (2025). A Comprehensive Survey on Tiny Machine Learning for Human Behavior Analysis. IEEE Internet of Things Journal. 12(16). 32419–32443. 18 indexed citations breakdown →
5.
Maleh, Yassine, et al.. (2025). A Systematic Review of State-of-the-Art TinyML Applications in Healthcare, Education, and Transportation. IEEE Access. 13. 204513–204562. 3 indexed citations
6.
Maleh, Yassine, Ibrahim Ouahbi, Khalid El Makkaoui, et al.. (2025). Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques. Sensors. 25(3). 812–812. 9 indexed citations
7.
Makkaoui, Khalid El, Ibrahim Ouahbi, Yassine Maleh, et al.. (2025). Tiny Deep Learning Models With Hybrid Compression Techniques for Gesture-Based Air Handwriting Recognition of English Alphabets on Edge Device. IEEE Internet of Things Journal. 13(1). 801–820. 3 indexed citations
8.
Makkaoui, Khalid El, et al.. (2025). TinyML vs LLMs: A Survey of Extreme Scales in Machine Learning. 1–6.
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Maleh, Yassine, et al.. (2025). Deep Learning Models for Detecting Cheating in Online Exams. Computers, materials & continua/Computers, materials & continua (Print). 85(2). 3151–3183. 5 indexed citations
12.
Maleh, Yassine, et al.. (2025). FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment. PLoS ONE. 20(11). e0332577–e0332577. 1 indexed citations
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Makkaoui, Khalid El, et al.. (2024). A TinyML model for sidewalk obstacle detection: aiding the blind and visually impaired people. Multimedia Tools and Applications. 84(22). 25837–25864. 2 indexed citations
15.
Ouahbi, Ibrahim, et al.. (2024). A deep learning-driven fingerprint verification model for enhancing exam integrity in Moroccan higher education. Information Security Journal A Global Perspective. 35(1). 40–52. 3 indexed citations
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Makkaoui, Khalid El, et al.. (2024). Enhancing Exam Integrity in Moroccan Higher Education: An AI-Based Fingerprint Verification Model. 1–5. 2 indexed citations
18.
Makkaoui, Khalid El, et al.. (2023). A LIGHTWEIGHT WHATSAPP END-TO-END ENCRYPTION. EDPACS. 67(6). 1–24. 1 indexed citations
19.
Ouahbi, Ibrahim, et al.. (2022). Visual Block-based Programming for ICT Training of Prospective Teachers in Morocco. International Journal of Modern Education and Computer Science. 14(1). 56–64. 4 indexed citations
20.
Ouahbi, Ibrahim, et al.. (2021). Gamification Approach in Teaching Web Programming Courses in PHP: Use of KAHOOT Application. International Journal of Modern Education and Computer Science. 13(2). 33–39. 10 indexed citations

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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