Yann Labit

504 citations
23 papers · 289 · h-index 10

Impact in

Papers in

    • Network Traffic and Congestion Control 11
    • Network Security and Intrusion Detection 9
    • Wireless Networks and Protocols 6
    • Software-Defined Networks and 5G 3
    • Internet Traffic Analysis and Secure E-voting 4
    • Anomaly Detection Techniques and Applications 3

Yann Labit

21 papers receiving 275 citations

Peers

Yann Labit
Comparison fields: 5 of 49
  • Computer Networks and Communications 167
  • Control and Systems Engineering 78
  • Automotive Engineering 24
  • Numerical Analysis 10
  • Artificial Intelligence 58
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Citations per field
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Citations per year

Countries citing papers authored by Yann Labit

Since Specialization
Citations

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

Fields of papers citing papers by Yann Labit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yann Labit, 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 Yann Labit Line = papers co-authored together Yann Labit links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004107
2 200929
3 201820
4 201117
5 201215
6 200914
7 201212
8 200611
9 20099
10 20109
11 20108
12 20228
13 20107
14 20086
15 20095
16 20092
17
1Network anomaly estimation for TCP/AQM networks using an observer
20152
18
Détection d'attaques de Dénis de Service par un modèle non gaussien multirésolution
20062
19 20202
20 20072

About Yann Labit

Yann Labit is a scholar working on Computer Networks and Communications, Artificial Intelligence, Control and Systems Engineering, Information Systems and Electrical and Electronic Engineering, having authored 23 papers that have together received 289 indexed citations. Recurring topics across this work include Network Traffic and Congestion Control (11 papers), Network Security and Intrusion Detection (9 papers), Wireless Networks and Protocols (6 papers), Internet Traffic Analysis and Secure E-voting (4 papers), Cloud Computing and Resource Management (3 papers), Software-Defined Networks and 5G (3 papers), Anomaly Detection Techniques and Applications (3 papers) and Advanced Wireless Network Optimization (2 papers). The work is most often cited by research in Computer Networks and Communications (167 citations), Control and Systems Engineering (78 citations), Automotive Engineering (24 citations), Numerical Analysis (10 citations) and Artificial Intelligence (58 citations). Yann Labit has collaborated with scholars based in France, Sweden and Spain. Frequent co-authors include Dimitri Peaucelle, Didier Henrion, Frédéric Gouaisbaut, Yassine Ariba, Philippe Owezarski, Johan Mazel, Thierry Floquet, Nicolas Larrieu, Georges Da Costa and Pedro Casas. Their work appears in journals such as IEEE Transactions on Network and Service Management, IET Control Theory and Applications, IEEE Transactions on Control Systems Technology, Simulation Modelling Practice and Theory and Computer Networks.

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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