Ibrahim Kamel

3.8k citations
129 papers · 2.1k · h-index 23

Impact in

Papers in

Ibrahim Kamel

119 papers receiving 1.9k citations

Peers

Ibrahim Kamel
Comparison fields: 5 of 111
  • Signal Processing 925
  • Computer Vision and Pattern Recognition 745
  • Computer Networks and Communications 793
  • Information Systems 515
  • Artificial Intelligence 563
Replace Chin‐Wan Chung with:
Chin‐Wan Chung South Korea
Dan Lin United States
Dmitri V. Kalashnikov United States
Marios Hadjieleftheriou United States
Feifei Li China
Haibo Hu Hong Kong
Renzo Angles Chile
Zhenjie Zhang China
Suh-Yin Lee Taiwan
Vassilis J. Tsotras United States
Ibrahim Kamel relative to Chin‐Wan Chung South Korea Chin‐Wan Chung's profile →
Citations per field
00.5×
Chin‐Wan Chung · 1×
Citations per year

Countries citing papers authored by Ibrahim Kamel

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Kamel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 129 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993304
2 1994164
3 2020131
4 1992105
5 201980
6 200370
7 201662
8 201854
9 200253
10 201643
11 201140
12 201839
13 200939
14 202339
15 201534
16 201933
17 202331
18
Nile-PDT: a phenomenon detection and tracking framework for data stream management systems
200530
19 202329
20 201728

About Ibrahim Kamel

Ibrahim Kamel is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Signal Processing and Information Systems, having authored 129 papers that have together received 2.1k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (29 papers), Data Management and Algorithms (21 papers), Chaos-based Image/Signal Encryption (16 papers), Digital Media Forensic Detection (16 papers), Cryptography and Data Security (11 papers), Robotic Path Planning Algorithms (10 papers), Advanced Database Systems and Queries (10 papers) and Peer-to-Peer Network Technologies (9 papers). The work is most often cited by research in Signal Processing (925 citations), Computer Vision and Pattern Recognition (745 citations), Computer Networks and Communications (793 citations), Information Systems (515 citations) and Artificial Intelligence (563 citations). Ibrahim Kamel has collaborated with scholars based in United Arab Emirates, United States and Egypt. Frequent co-authors include Christos Faloutsos, Tamer Rabie, Zaher Al Aghbari, Walid G. Aref, Mohammed Baziyad, Djedjiga Mouheb, Mohamed F. Mokbel, Khaled Shaalan, Rafael Alonso and Wenjun Zeng. Their work appears in journals such as Multimedia Tools and Applications, IEEE Access, GeoInformatica, Distributed and Parallel Databases and IEEE Transactions on Multimedia.

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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