Fahed Abdallah

1.4k total citations
53 papers, 861 citations indexed

About

Fahed Abdallah is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Fahed Abdallah has authored 53 papers receiving a total of 861 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 23 papers in Computer Vision and Pattern Recognition and 8 papers in Control and Systems Engineering. Recurrent topics in Fahed Abdallah's work include Face and Expression Recognition (12 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Video Surveillance and Tracking Methods (7 papers). Fahed Abdallah is often cited by papers focused on Face and Expression Recognition (12 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Video Surveillance and Tracking Methods (7 papers). Fahed Abdallah collaborates with scholars based in France, Lebanon and Luxembourg. Fahed Abdallah's co-authors include Amadou Gning, Thierry Denœux, Philippe Bonnifait, Hichem Snoussi, Fadi Dornaika, Caroline Petitjean, Paul Honeiné, Lyudmila Mihaylova, Cédric Richard and Hichem Omrani and has published in prestigious journals such as Automatica, IEEE Transactions on Signal Processing and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Fahed Abdallah

50 papers receiving 836 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fahed Abdallah France 17 433 284 95 88 87 53 861
En Fan China 11 271 0.6× 236 0.8× 89 0.9× 69 0.8× 55 0.6× 44 974
Yang Lu China 20 463 1.1× 577 2.0× 100 1.1× 75 0.9× 103 1.2× 106 1.3k
Abdussalam Elhanashi Italy 19 304 0.7× 393 1.4× 147 1.5× 63 0.7× 78 0.9× 36 1.1k
Wei Song China 13 243 0.6× 337 1.2× 110 1.2× 104 1.2× 78 0.9× 96 833
Mingyang Zhang China 27 512 1.2× 515 1.8× 97 1.0× 51 0.6× 142 1.6× 118 2.0k
Cheng Tan China 12 325 0.8× 250 0.9× 70 0.7× 49 0.6× 39 0.4× 41 1.0k
Kewen Xia China 20 353 0.8× 272 1.0× 258 2.7× 81 0.9× 150 1.7× 126 1.3k
Yang Xu China 19 290 0.7× 478 1.7× 78 0.8× 72 0.8× 129 1.5× 121 1.5k
Hongmin Gao China 27 265 0.6× 576 2.0× 163 1.7× 54 0.6× 239 2.7× 173 2.0k
Liguo Weng China 19 286 0.7× 308 1.1× 82 0.9× 70 0.8× 77 0.9× 73 979

Countries citing papers authored by Fahed Abdallah

Since Specialization
Citations

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

Fields of papers citing papers by Fahed Abdallah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fahed Abdallah

This figure shows the co-authorship network connecting the top 25 collaborators of Fahed Abdallah. A scholar is included among the top collaborators of Fahed Abdallah 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 Fahed Abdallah. Fahed Abdallah 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.
Fasquel, Jean-Baptiste, et al.. (2024). Multi-View Graph Neural Network for Semantic Image Segmentation. SPIRE - Sciences Po Institutional REpository. 1–6.
2.
Abdallah, Fahed, et al.. (2024). Deep Clustering for Epileptic Seizure Detection. IEEE Transactions on Biomedical Engineering. 72(2). 480–492. 2 indexed citations
3.
Abdallah, Fahed, et al.. (2024). One-step graph-based multi-view clustering via specific and unified nonnegative embeddings. International Journal of Machine Learning and Cybernetics. 15(12). 5807–5822.
4.
Abdallah, Fahed, et al.. (2024). Cross-Site Generalization Using Attention Layer for Epileptic Seizure Detection. 1571–1575. 1 indexed citations
5.
Dornaika, Fadi, et al.. (2024). Recognizing and detecting COVID-19 in chest X-ray images using constrained multi-view spectral clustering. Progress in Artificial Intelligence. 2 indexed citations
6.
Abdallah, Fahed, et al.. (2024). A Novel Unsupervised Approach for Accurate Epileptic Seizure Detection. 1426–1430. 2 indexed citations
7.
Kassem, Hassan, et al.. (2024). Multi-view Deep Embedded Clustering: Exploring a new dimension of air pollution. Engineering Applications of Artificial Intelligence. 139. 109509–109509. 1 indexed citations
8.
Abdallah, Fahed, et al.. (2023). Long Short-Term Memory and Attention Models for Simulating Urban Densification. Sustainable Cities and Society. 98. 104852–104852. 6 indexed citations
9.
Abdallah, Fahed, et al.. (2023). A self-attention model for cross-subject seizure detection. Computers in Biology and Medicine. 165. 107427–107427. 9 indexed citations
10.
Kassem, Hassan, et al.. (2023). Enhancing building segmentation by deep multiview classification for advancing sustainable urban development. Journal of Building Engineering. 83. 108421–108421. 3 indexed citations
11.
Petitjean, Caroline, et al.. (2021). High-level prior-based loss functions for medical image segmentation: A survey. Computer Vision and Image Understanding. 210. 103248–103248. 65 indexed citations
12.
Dornaika, Fadi, et al.. (2021). Multi-view spectral clustering via constrained nonnegative embedding. Information Fusion. 78. 209–217. 51 indexed citations
13.
Petitjean, Caroline, et al.. (2020). BB-UNet: U-Net With Bounding Box Prior. IEEE Journal of Selected Topics in Signal Processing. 14(6). 1189–1198. 45 indexed citations
14.
Omrani, Hichem, Fahed Abdallah, Amin Tayyebi, & Bryan C. Pijanowski. (2017). Modelling land-use change with dependence among labels.. Journal of Environmental Informatics. 30(2). 107–118. 7 indexed citations
15.
Qin, Lei, Hichem Snoussi, & Fahed Abdallah. (2014). Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance. Sensors. 14(6). 9380–9407. 10 indexed citations
16.
Abdallah, Fahed, et al.. (2012). Purifying training data to improve performance of multi-label classification algorithms. International Conference on Information Fusion. 1784–1791. 2 indexed citations
17.
Denœux, Thierry, et al.. (2010). Representing uncertainty on set-valued variables using belief functions. Artificial Intelligence. 174(7-8). 479–499. 33 indexed citations
18.
Abdallah, Fahed, et al.. (2009). State Estimation Using Interval Analysis and Belief-Function Theory: Application to Dynamic Vehicle Localization. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 40(5). 1205–1218. 40 indexed citations
19.
Abdallah, Fahed, et al.. (2008). Map matching algorithm using belief function theory. International Conference on Information Fusion. 1–8. 14 indexed citations
20.
Abdallah, Fahed, Amadou Gning, & Philippe Bonnifait. (2007). Box particle filtering for nonlinear state estimation using interval analysis. Automatica. 44(3). 807–815. 111 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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