Mohamed Hamada

1.5k citations
100 papers · 908 · h-index 18

Impact in

Papers in

Mohamed Hamada

94 papers receiving 854 citations

Peers

Mohamed Hamada
Comparison fields: 5 of 115
  • Computer Science Applications 121
  • Health Information Management 66
  • Computational Mathematics 9
  • Computer Vision and Pattern Recognition 254
  • Information Systems 267
Replace Teguh Bharata Adji with:
Teguh Bharata Adji Indonesia
Sellappan Palaniappan Malaysia
Mihaela Cocea United Kingdom
Muhammad Wasif Nisar Pakistan
Derek F. Wong Macao
Shailendra Narayan Singh India
Fred Hohman United States
Marie desJardins United States
Selma Ayşe Özel Türkiye
Hui-Huang Hsu Taiwan
Mohamed Hamada relative to Teguh Bharata Adji Indonesia Teguh Bharata Adji's profile →
Citations per field
00.5×2.8×
Teguh Bharata Adji · 1×
Citations per year

Countries citing papers authored by Mohamed Hamada

Since Specialization
Citations

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

Fields of papers citing papers by Mohamed Hamada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202273
2 201953
3 201753
4 202241
5 201638
6 201732
7 201827
8 202125
9 200825
10 201722
11 202019
12 202219
13 201619
14 201719
15 202217
16 202117
17 202117
18 200717
19 201716
20 201615

About Mohamed Hamada

Mohamed Hamada is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Science Applications and Developmental and Educational Psychology, having authored 100 papers that have together received 908 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (16 papers), Advanced Data Compression Techniques (11 papers), Online Learning and Analytics (9 papers), Learning Styles and Cognitive Differences (9 papers), Image Retrieval and Classification Techniques (8 papers), Open Education and E-Learning (7 papers), Algorithms and Data Compression (7 papers) and Intelligent Tutoring Systems and Adaptive Learning (7 papers). The work is most often cited by research in Computer Science Applications (121 citations), Health Information Management (66 citations), Computational Mathematics (9 citations), Computer Vision and Pattern Recognition (254 citations) and Information Systems (267 citations). Mohamed Hamada has collaborated with scholars based in Japan, Nigeria and Egypt. Frequent co-authors include Mohammed Hassan, Md. Atiqur Rahman, Mohamed G. Hassan, Jungpil Shin, Farouq Aliyu, Md. Imtaiyaz Hassan, Anand Mahendran, Nkiruka Odu, Hazem M. El‐Bakry and Rajesh Prasad. Their work appears in journals such as Applied Sciences, Electronics, IEEE Access, Symmetry 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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