Hela Ltifi

896 total citations
64 papers, 424 citations indexed

About

Hela Ltifi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Hela Ltifi has authored 64 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 27 papers in Computer Vision and Pattern Recognition and 12 papers in Signal Processing. Recurrent topics in Hela Ltifi's work include Data Visualization and Analytics (20 papers), Neural Networks and Reservoir Computing (12 papers) and Neural Networks and Applications (9 papers). Hela Ltifi is often cited by papers focused on Data Visualization and Analytics (20 papers), Neural Networks and Reservoir Computing (12 papers) and Neural Networks and Applications (9 papers). Hela Ltifi collaborates with scholars based in Tunisia, France and Sweden. Hela Ltifi's co-authors include Mounir Ben Ayed, Christophe Kolski, Adel M. Alimi, Sophie Lepreux, Mohamed Masmoudi, Mohamed Elleuch, Monji Kherallah and Wael Ouarda and has published in prestigious journals such as IEEE Access, Decision Support Systems and Knowledge-Based Systems.

In The Last Decade

Hela Ltifi

55 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hela Ltifi Tunisia 13 156 144 49 45 43 64 424
Prableen Kaur India 5 227 1.5× 56 0.4× 23 0.5× 25 0.6× 55 1.3× 9 474
Brojo Kishore Mishra India 14 220 1.4× 121 0.8× 19 0.4× 15 0.3× 115 2.7× 79 607
Sushma Jaiswal India 11 69 0.4× 111 0.8× 15 0.3× 13 0.3× 42 1.0× 63 360
Mehul Bhatt Germany 14 270 1.7× 89 0.6× 24 0.5× 25 0.6× 141 3.3× 57 566
Mohamed Ben Halima Tunisia 11 114 0.7× 277 1.9× 18 0.4× 21 0.5× 13 0.3× 31 435
Faisal Ahmed Bangladesh 10 386 2.5× 367 2.5× 10 0.2× 49 1.1× 32 0.7× 32 739
Navarun Gupta United States 6 58 0.4× 25 0.2× 68 1.4× 34 0.8× 43 1.0× 28 265
Cun Ji China 14 253 1.6× 54 0.4× 16 0.3× 41 0.9× 43 1.0× 47 471
Lingling Zhao China 12 142 0.9× 83 0.6× 18 0.4× 50 1.1× 76 1.8× 30 361
Fatima Alshehri Saudi Arabia 4 113 0.7× 75 0.5× 10 0.2× 37 0.8× 120 2.8× 6 420

Countries citing papers authored by Hela Ltifi

Since Specialization
Citations

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

Fields of papers citing papers by Hela Ltifi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hela Ltifi

This figure shows the co-authorship network connecting the top 25 collaborators of Hela Ltifi. A scholar is included among the top collaborators of Hela Ltifi 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 Hela Ltifi. Hela Ltifi 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
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Ltifi, Hela, et al.. (2025). Advanced Brain Tumor Segmentation With a Multiscale CNN and Conditional Random Fields. IEEE Access. 13. 34925–34935. 1 indexed citations
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Ltifi, Hela, et al.. (2024). Newman-Watts-Strogatz topology in deep echo state networks for speech emotion recognition. Engineering Applications of Artificial Intelligence. 133. 108293–108293. 8 indexed citations
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Ltifi, Hela, et al.. (2024). Sentiment analysis deep learning model based on a novel hybrid embedding method. Social Network Analysis and Mining. 14(1). 2 indexed citations
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Ltifi, Hela, et al.. (2024). Hybrid Quanvolutional Echo State Network for Time Series Prediction. 40–46. 1 indexed citations
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Ltifi, Hela, et al.. (2023). Novel diversified echo state network for improved accuracy and explainability of EEG-based stroke prediction. Information Systems. 120. 102317–102317. 8 indexed citations
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Ltifi, Hela, et al.. (2023). Deep Learning and Machine Learning for Malaria Detection: Overview, Challenges and Future Directions. International Journal of Information Technology & Decision Making. 23(5). 1745–1776. 27 indexed citations
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Ltifi, Hela, et al.. (2023). PSO-K2PC: Bayesian structure learning using optimized K2 algorithm for parents-children detection. International Journal of Computers and Applications. 45(9). 553–563. 1 indexed citations
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Ltifi, Hela, et al.. (2023). Echo State Network Optimization: A Systematic Literature Review. Neural Processing Letters. 55(8). 10251–10285. 7 indexed citations
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Ltifi, Hela, et al.. (2022). Improving Malaria Detection Using L1 Regularization Neural Network. JUCS - Journal of Universal Computer Science. 28(10). 1087–1107. 12 indexed citations
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Ltifi, Hela, et al.. (2022). A Novel Deep Multi-Task Learning to Sensing Student Engagement in E-Learning Environments. 8228. 1–7. 1 indexed citations
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Ltifi, Hela, et al.. (2020). Intelligent health monitoring system modeling based on machine learning and agent technology. Multiagent and Grid Systems. 16(2). 207–226. 9 indexed citations
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Ltifi, Hela, Mounir Ben Ayed, Adel M. Alimi, & Sophie Lepreux. (2009). Survey of information visualization techniques for exploitation in KDD. 218–225. 20 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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