Riadh Ksantini

969 citations
72 papers · 568 indexed · h-index 13

Riadh Ksantini

65 papers receiving 538 citations

Peers

Riadh Ksantini
Comparison fields: 5 of 98
  • Computer Vision and Pattern Recognition 200
  • Artificial Intelligence 242
  • Signal Processing 60
  • Statistical and Nonlinear Physics 44
  • Media Technology 31
Replace Bingbing Jiang with:
Bingbing Jiang China
Younès Bennani France
Hong-Jie Xing China
Grigorios Tzortzis Greece
Dylan Anderson United States
Erxue Min China
Hongmei Wang China
Xujun Zhao China
Jianjing Cui China
Ye Yuan China
Riadh Ksantini relative to Bingbing Jiang China Bingbing Jiang's profile →
Citations per field
00.5×1.5×2.3×
Bingbing Jiang · 1×
Citations per year

Countries citing papers authored by Riadh Ksantini

Since Specialization
Citations

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

Fields of papers citing papers by Riadh Ksantini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 21 scholars most cited alongside Riadh Ksantini, 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 Riadh Ksantini Line = papers co-authored together Riadh Ksantini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20241
3 20240
4 202413
5 20239
6 20230
7 20231
8 20221
9 202117
10 20211
11 20211
12 20212
13 202138
14 202054
15 20191
16 20189
17 20100
18 20097
19
A Bayesian Kernel logistic discriminant model: an improvement to the Kernel Fisher's discriminant
20080
20 200723

About Riadh Ksantini

Riadh Ksantini is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 72 papers that have together received 568 indexed citations. Recurring topics across this work include Face and Expression Recognition (16 papers), Anomaly Detection Techniques and Applications (13 papers), Machine Learning and ELM (9 papers), Network Security and Intrusion Detection (7 papers), Image Retrieval and Classification Techniques (7 papers), Geophysical Methods and Applications (6 papers), AI in cancer detection (5 papers) and Remote-Sensing Image Classification (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (200 citations), Artificial Intelligence (242 citations) and Signal Processing (60 citations). Riadh Ksantini has collaborated with scholars based in Canada, Bahrain and Tunisia. Frequent co-authors include Naimul Khan, Zied Lachiri, Boubakeur Boufama, Mohamed Bouguessa, François Dubeau, Ling Guan, Djemel Ziou, Adel Bouhoula, Wael Elmedany and Mohamed Kaâniche. Their work appears in journals such as Pattern Recognition, International Journal of Remote Sensing, Neural Networks, International Journal of Machine Learning and Cybernetics and Journal of the Optical Society of America A.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026