Gérard Memmi

37 papers receiving 1.1k citations

Peers

Gérard Memmi
Comparison fields: 5 of 85
  • Hardware and Architecture 285
  • Computer Networks and Communications 370
  • Information Systems 340
  • Signal Processing 156
  • Artificial Intelligence 381
Replace Parag Kulkarni with:
Parag Kulkarni India
Sibin Mohan United States
Kaiyuan Zhang China
Jingqiang Lin China
Peter Kilpatrick United Kingdom
Ruhui Ma China
Lejla Batina Netherlands
Arquimedes Canedo United States
Yoohwan Kim United States
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Citations per year

Countries citing papers authored by Gérard Memmi

Since Specialization
Citations

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

Fields of papers citing papers by Gérard Memmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006205
2 2020183
3 2020152
4 202099
5 202085
6 201980
7 201946
8 202043
9 200637
10 201934
11 198231
12 198521
13 202121
14 201913
15 201911
16 201410
17 202310
18 20249
19 20227
20 20237

About Gérard Memmi

Gérard Memmi is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 41 papers that have together received 1.2k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (6 papers), Adversarial Robustness in Machine Learning (6 papers), Cryptography and Data Security (5 papers), Advanced Malware Detection Techniques (5 papers), Advanced Steganography and Watermarking Techniques (4 papers), Embedded Systems Design Techniques (4 papers), Cloud Data Security Solutions (4 papers) and Privacy-Preserving Technologies in Data (4 papers). The work is most often cited by research in Hardware and Architecture (285 citations), Computer Networks and Communications (370 citations), Information Systems (340 citations), Signal Processing (156 citations) and Artificial Intelligence (381 citations). Gérard Memmi has collaborated with scholars based in France, China and United States. Frequent co-authors include Han Qiu, Meikang Qiu, Jialiang Lu, Tianwei Zhang, P. Bradley, M. Abramovici, Peter Levin, Meiqin Liu, Qinkai Zheng and Mounira Msahli. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Transactions on Intelligent Transportation Systems, Computer Physics Communications, Sustainable Computing Informatics and Systems and Information Sciences.

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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