Mohamed Ksantini

468 total citations
32 papers, 287 citations indexed

About

Mohamed Ksantini is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mohamed Ksantini has authored 32 papers receiving a total of 287 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Control and Systems Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mohamed Ksantini's work include Stability and Control of Uncertain Systems (8 papers), Fuzzy Logic and Control Systems (7 papers) and Gallbladder and Bile Duct Disorders (4 papers). Mohamed Ksantini is often cited by papers focused on Stability and Control of Uncertain Systems (8 papers), Fuzzy Logic and Control Systems (7 papers) and Gallbladder and Bile Duct Disorders (4 papers). Mohamed Ksantini collaborates with scholars based in Tunisia, France and Saudi Arabia. Mohamed Ksantini's co-authors include François Delmotte, Thierry‐Marie Guerra, Hatem Bellâaj, Omar Kahouli, Haitham Alsaif, Sohaib Ahmed, Bassem Kahouli, Saleh Albadran, Mohamed Chtourou and Jimmy Lauber and has published in prestigious journals such as IEEE Access, IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems.

In The Last Decade

Mohamed Ksantini

29 papers receiving 274 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohamed Ksantini Tunisia 9 113 77 56 42 31 32 287
Weimin Huang China 11 46 0.4× 165 2.1× 138 2.5× 27 0.6× 44 1.4× 28 367
Ali Alqahtani Saudi Arabia 12 21 0.2× 121 1.6× 68 1.2× 115 2.7× 45 1.5× 46 380
Md. Al-Masrur Khan Bangladesh 8 19 0.2× 55 0.7× 54 1.0× 74 1.8× 11 0.4× 13 329
L. Madarász Slovakia 10 191 1.7× 64 0.8× 30 0.5× 36 0.9× 11 0.4× 66 331
Shreesha Chokkadi India 8 88 0.8× 72 0.9× 163 2.9× 7 0.2× 46 1.5× 40 343
Jinxin Liu China 12 98 0.9× 75 1.0× 80 1.4× 20 0.5× 25 0.8× 34 392
Yüksel Çelik Türkiye 10 29 0.3× 105 1.4× 41 0.7× 46 1.1× 38 1.2× 32 313
Eman M. El-Gendy Egypt 13 37 0.3× 196 2.5× 110 2.0× 12 0.3× 95 3.1× 24 451
Bowen Liu China 11 175 1.5× 67 0.9× 40 0.7× 28 0.7× 73 2.4× 43 395
Hamid Ghadiri Iran 10 197 1.7× 47 0.6× 30 0.5× 56 1.3× 10 0.3× 25 310

Countries citing papers authored by Mohamed Ksantini

Since Specialization
Citations

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

Fields of papers citing papers by Mohamed Ksantini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohamed Ksantini

This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Ksantini. A scholar is included among the top collaborators of Mohamed Ksantini 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 Mohamed Ksantini. Mohamed Ksantini 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.
Ksantini, Mohamed, et al.. (2024). Improvement of Smart Grid Stability Based on Artificial Intelligence with Fusion Methods. Symmetry. 16(4). 459–459. 10 indexed citations
2.
Ksantini, Mohamed, et al.. (2024). An Advanced Approach for Predicting ROP Stages: Deep Learning Algorithms and Belief Function Technique. Iraqi Journal of Science. 4047–4060.
3.
Ksantini, Mohamed, et al.. (2024). Facial Expression-Based Drowsiness Detection System for Driver Safety Using Deep Learning Techniques. SPIRE - Sciences Po Institutional REpository. 726–733. 1 indexed citations
4.
Ksantini, Mohamed, et al.. (2024). A Comprehensive Survey and Analysis of Traffic Sign Recognition Systems With Hardware Implementation. IEEE Access. 12. 144069–144081. 2 indexed citations
5.
Ksantini, Mohamed, et al.. (2024). New Speed Limit Recognition System: Software and Hardware Validation. SPIRE - Sciences Po Institutional REpository. 368–375. 1 indexed citations
6.
Ksantini, Mohamed, et al.. (2024). A New Speed Limit Recognition Methodology Based on Ensemble Learning: Hardware Validation. Computers, materials & continua/Computers, materials & continua (Print). 80(1). 119–138.
7.
Ksantini, Mohamed, et al.. (2024). Catalyzing early intervention: A robust deep learning approach for detecting retinopathy of prematurity and plus diseases in infants. Journal of Autonomous Intelligence. 7(5). 1589–1589. 1 indexed citations
8.
Ksantini, Mohamed, et al.. (2024). Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners: A Recommendation System. Computers, materials & continua/Computers, materials & continua (Print). 79(1). 351–372. 3 indexed citations
9.
Bellâaj, Hatem, et al.. (2024). UIdataGB: Multi-Class ultrasound images dataset for gallbladder disease detection. Data in Brief. 54. 110426–110426. 5 indexed citations
10.
Ksantini, Mohamed, et al.. (2023). A Real-Time Traffic Sign Recognition Method Using a New Attention-Based Deep Convolutional Neural Network for Smart Vehicles. Applied Sciences. 13(8). 4793–4793. 45 indexed citations
11.
Ksantini, Mohamed, et al.. (2023). Deep Learning Models and Fusion Classification Technique for Accurate Diagnosis of Retinopathy of Prematurity in Preterm Newborn. Baghdad Science Journal. 21(5). 1729–1729. 4 indexed citations
12.
Ksantini, Mohamed, et al.. (2023). Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique. International Journal of Computational Intelligence Systems. 16(1). 9 indexed citations
13.
Bellâaj, Hatem, et al.. (2023). Detection of Gallbladder Disease Types Using Deep Learning: An Informative Medical Method. Diagnostics. 13(10). 1744–1744. 21 indexed citations
14.
Ksantini, Mohamed, et al.. (2022). New LSTM Deep Learning Algorithm for Driving Behavior Classification. Cybernetics & Systems. 54(4). 387–405. 19 indexed citations
15.
Bellâaj, Hatem, et al.. (2022). Detection of Biliary Artesia using Sonographic Gallbladder Images with the help of Deep Learning approaches. 2022 8th International Conference on Control, Decision and Information Technologies (CoDIT). 705–711. 5 indexed citations
16.
Kahouli, Omar, et al.. (2022). Artificial Intelligence-Based Diabetes Diagnosis with Belief Functions Theory. Symmetry. 14(10). 2197–2197. 10 indexed citations
17.
Ksantini, Mohamed, et al.. (2021). Traffic Sign Recognition System based on Belief Functions Theory. SPIRE - Sciences Po Institutional REpository. 775–780. 4 indexed citations
18.
Ksantini, Mohamed, et al.. (2020). Artificial Intelligence Prediction Algorithms for Future Evolution of COVID-19 Cases. Ingénierie des systèmes d information. 25(3). 319–325. 2 indexed citations
19.
Ksantini, Mohamed, et al.. (2019). Asymptoyic behavior of Takagi-Sugeno fuzzy control systems with bounded uncertainties. 108–112. 1 indexed citations
20.
Ksantini, Mohamed, et al.. (2013). Control of a hydraulic system by means of a fuzzy approach. An International Journal of Optimization and Control Theories & Applications (IJOCTA). 3(2). 121–131. 4 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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