Nabil Layaïda

1.4k citations
53 papers · 480 · h-index 12

Impact in

Papers in

Nabil Layaïda

47 papers receiving 418 citations

Peers

Nabil Layaïda
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 224
  • Computer Networks and Communications 225
  • Information Systems 153
  • Software 19
  • Artificial Intelligence 149
Replace Vinod Anupam with:
Vinod Anupam United States
Benjamin Aziz United Kingdom
Ian Oliver Finland
Peter Gutmann New Zealand
K. Maly United States
Peter Ørbæk Denmark
Ignac Lovrek Croatia
Dongwan Shin United States
Rachid Hadjidj Canada
Tan Soo Fun Malaysia
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Citations per field
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Citations per year

Countries citing papers authored by Nabil Layaïda

Since Specialization
Citations

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

Fields of papers citing papers by Nabil Layaïda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Nabil Layaïda, 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 Nabil Layaïda Line = papers co-authored together Nabil Layaïda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200485
2 199871
3 200333
4 201827
5 200221
6 200618
7 200217
8 201015
9 201114
10
A semantic framework for multimedia document adaptation
200314
11 199612
12 199711
13 200311
14
Universal Profiling for Content Negotiation and Adaptation in Heterogeneous Environments
20029
15 20058
16 19978
17 20188
18 20187
19 20097
20 20117

About Nabil Layaïda

Nabil Layaïda is a scholar working on Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science, Computer Vision and Pattern Recognition and Information Systems, having authored 53 papers that have together received 480 indexed citations. Recurring topics across this work include Multimedia Communication and Technology (17 papers), Logic, programming, and type systems (14 papers), Video Analysis and Summarization (14 papers), Advanced Database Systems and Queries (14 papers), Semantic Web and Ontologies (11 papers), Logic, Reasoning, and Knowledge (9 papers), Formal Methods in Verification (9 papers) and Peer-to-Peer Network Technologies (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (224 citations), Computer Networks and Communications (225 citations), Information Systems (153 citations), Software (19 citations) and Artificial Intelligence (149 citations). Nabil Layaïda has collaborated with scholars based in France, United States and Switzerland. Frequent co-authors include Tayeb Lemlouma, Pierre Genevès, Cécile Roisin, Muriel Jourdan, Jérôme Euzenat, Lionel Villard, Hassen Fourati, Vincent Quint, Alan Schmitt and Sébastien Laborie. Their work appears in journals such as ACM SIGPLAN Notices, ACM Transactions on Internet Technology, Multimedia Tools and Applications, ACM Transactions on Information Systems and ACM Transactions on Multimedia Computing Communications and Applications.

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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