Ameur Benséfia

8 papers and 179 indexed citations i.

About

Ameur Benséfia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Ameur Benséfia has authored 8 papers receiving a total of 179 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Cognitive Neuroscience. Recurrent topics in Ameur Benséfia’s work include Image Processing and 3D Reconstruction (4 papers), Handwritten Text Recognition Techniques (4 papers) and Natural Language Processing Techniques (3 papers). Ameur Benséfia is often cited by papers focused on Image Processing and 3D Reconstruction (4 papers), Handwritten Text Recognition Techniques (4 papers) and Natural Language Processing Techniques (3 papers). Ameur Benséfia collaborates with scholars based in United Arab Emirates, France and Pakistan. Ameur Benséfia's co-authors include Thierry Paquet, Laurent Heutte, Imran Siddiqi, Abdeljalil Gattal, Kamel Saoudi and Chawki Djeddi and has published in prestigious journals such as Pattern Recognition Letters, EURASIP Journal on Image and Video Processing and IET Biometrics.

In The Last Decade

Co-authorship network of co-authors of Ameur Benséfia i

Fields of papers citing papers by Ameur Benséfia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Ameur Benséfia

Since Specialization
Citations

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

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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