Mohammed Al-Shabi

498 citations
24 papers · 291 indexed · h-index 9
Topics
Network Security and Intrusion Detection (3 papers)IoT and Edge/Fog Computing (3 papers)COVID-19 diagnosis using AI (3 papers)
Journals
SHILAP Revista de lepidopterologíaApplied SciencesMultimedia Tools and Applications

In The Last Decade

Mohammed Al-Shabi

20 papers receiving 275 citations

Peers

Mohammed Al-Shabi
Comparison fields: 5 of 69
  • Artificial Intelligence 124
  • Computer Networks and Communications 91
  • Information Systems 84
  • Computer Vision and Pattern Recognition 58
  • Electrical and Electronic Engineering 41
Replace Khaled Alhazmi with:
Khaled Alhazmi Saudi Arabia
Anup Mohan United States
Fahd S. Alharithi Saudi Arabia
Yogesh Kumar India
Dilli Ganesh India
Y. C. A. Padmanabha Reddy India
Nidhi Sindhwani India
Manel Ayadi Saudi Arabia
Gaojuan Fan China
R. Saravanan India
Mohammed Al-Shabi relative to Khaled Alhazmi Saudi Arabia Khaled Alhazmi's profile →
Citations per field
00.5×1.5×2.2×
Khaled Alhazmi · 1×
Citations per year

Countries citing papers authored by Mohammed Al-Shabi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed Al-Shabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed Al-Shabi. 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 Mohammed Al-Shabi. The network helps show where Mohammed Al-Shabi may publish in the future.

Co-authorship network of co-authors of Mohammed Al-Shabi

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Al-Shabi. A scholar is included among the top collaborators of Mohammed Al-Shabi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohammed Al-Shabi. Mohammed Al-Shabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3 0
4 10
5 1
6 4
7 0
8 4
9 37
10 12
11 7
12 1
13 17
14 6
15 55
16 49
17
Global Behavior of a Fourth Order Rational Difference Equation
2
18 1
19 4
20 6

About Mohammed Al-Shabi

Mohammed Al-Shabi is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 24 papers that have together received 291 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (3 papers), IoT and Edge/Fog Computing (3 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Computer Networks and Communications (91 citations), Artificial Intelligence (124 citations) and Information Systems (84 citations). Mohammed Al-Shabi has collaborated with scholars based in Saudi Arabia, United Arab Emirates and United Kingdom. Frequent co-authors include Abdulrahman Alqarafi, Fahd N. Al‐Wesabi, Mesfer Al Duhayyim, Feras Barneih, Nida Nasir, Talal Bonny, Fadwa Alrowais, Nadhem Nemri, Mahmoud Othman and Saud S. Alotaibi. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Sciences and Multimedia Tools 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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