M. A. El-Dosuky

21 papers receiving 207 citations

Peers

M. A. El-Dosuky
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 41
  • Artificial Intelligence 58
  • Energy Engineering and Power Technology 5
  • Health Information Management 5
  • Aerospace Engineering 23
Replace Md. Faisal Ahmed with:
Md. Faisal Ahmed South Korea
Mingwei Li China
Hazem Migdady Jordan
Saidul Islam United Arab Emirates
Hanae Elmekki Canada
Gandikota Ramu India
Armin Masoumian Spain
R. Kanthavel Saudi Arabia
Isha Kansal India
Manuel Castillo‐Cara Spain
M. A. El-Dosuky relative to Md. Faisal Ahmed South Korea Md. Faisal Ahmed's profile →
Citations per field
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Citations per year

Countries citing papers authored by M. A. El-Dosuky

Since Specialization
Citations

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

Fields of papers citing papers by M. A. El-Dosuky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. A. El-Dosuky. 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 M. A. El-Dosuky. The network helps show where M. A. El-Dosuky may publish in the future.

Co-authors

The 22 scholars most cited alongside M. A. El-Dosuky, 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 M. A. El-Dosuky Line = papers co-authored together M. A. El-Dosuky links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201470
2 202246
3 202318
4 202215
5 202413
6 201610
7 202110
8 20247
9
FAFSA: Fast Artificial Fish Swarm Algorithm
20135
10 20254
11
Subject Recommendation Using Ontology for Computer Science ACM Curricula
20144
12 20193
13 20163
14 20192
15 20171
16 20201
17 20201
18 20141
19 20141
20 20161

About M. A. El-Dosuky

M. A. El-Dosuky is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Aerospace Engineering and Electrical and Electronic Engineering, having authored 30 papers that have together received 219 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (3 papers), Energy Load and Power Forecasting (3 papers), Robotic Path Planning Algorithms (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Artificial Immune Systems Applications (2 papers), UAV Applications and Optimization (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (41 citations), Artificial Intelligence (58 citations), Energy Engineering and Power Technology (5 citations), Health Information Management (5 citations) and Aerospace Engineering (23 citations). M. A. El-Dosuky has collaborated with scholars based in Egypt, Saudi Arabia and Kuwait. Frequent co-authors include Aboul Ella Hassanien, Mahmoud Y. Shams, Ahmed M. Elshewey, Zahraa Tarek, El‐Sayed M. El‐kenawy, Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Abdelaziz A. Abdelhamid, Ashraf Darwish, M. Z. Rashad and Mona Soliman. Their work appears in journals such as International Journal of Imaging Systems and Technology, Scientific Reports, Applied Soft Computing, Drones and Neural Computing 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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