Rafik Hamza

1.4k citations
25 papers · 1.0k · h-index 14

Impact in

Papers in

Rafik Hamza

23 papers receiving 980 citations

Peers

Rafik Hamza
Comparison fields: 5 of 81
  • Computer Vision and Pattern Recognition 557
  • Information Systems 284
  • Artificial Intelligence 347
  • Computer Networks and Communications 224
  • Signal Processing 76
Replace Xiaoqiang Di with:
Xiaoqiang Di China
Prabhakar Krishnan India
Amjad Hussain Zahid Pakistan
Dmitri Botvich Ireland
Ahmet Zengi̇n Türkiye
Qirong Ho United States
Tung-Shou Chen Taiwan
Qinyong Wang China
Yanfeng Zhang China
Rafik Hamza relative to Xiaoqiang Di China Xiaoqiang Di's profile →
Citations per field
00.5×7.4×
Xiaoqiang Di · 1×
Citations per year

Countries citing papers authored by Rafik Hamza

Since Specialization
Citations

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

Fields of papers citing papers by Rafik Hamza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018210
2 2019145
3 202287
4 201783
5 201977
6 201668
7 202066
8 201760
9 201759
10 202238
11 201936
12 201928
13 202216
14 202215
15 202213
16 20229
17 20218
18 20253
19 20233
20 20202

About Rafik Hamza

Rafik Hamza is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Computer Networks and Communications and Computational Theory and Mathematics, having authored 25 papers that have together received 1.0k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (11 papers), Advanced Steganography and Watermarking Techniques (10 papers), Privacy-Preserving Technologies in Data (7 papers), Blockchain Technology Applications and Security (6 papers), Cryptography and Data Security (5 papers), IoT and Edge/Fog Computing (3 papers), Cloud Computing and Resource Management (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (557 citations), Information Systems (284 citations), Artificial Intelligence (347 citations), Computer Networks and Communications (224 citations) and Signal Processing (76 citations). Rafik Hamza has collaborated with scholars based in Japan, Algeria and China. Frequent co-authors include Khan Muhammad, Faiza Titouna, Hongyang Yan, Jamil Ahmad, Haoxiang Wang, Sung Wook Baik, Alzubair Hassan, Jaime Lloret, Paolo Bellavista and Zheng Yan. Their work appears in journals such as IEEE Access, Sensors, Pervasive and Mobile Computing, Engineering Applications of Artificial Intelligence and Scientific Reports.

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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