M. Talib

602 citations
25 papers · 357 · h-index 13

Impact in

Papers in

M. Talib

21 papers receiving 329 citations

Peers

M. Talib
Comparison fields: 5 of 73
  • Computer Networks and Communications 100
  • Linguistics and Language 19
  • Signal Processing 40
  • Information Systems 79
  • Computer Vision and Pattern Recognition 68
Replace Jedrzej Rybicki with:
Jedrzej Rybicki Germany
Nikhat Akhtar India
Srinath Doss Botswana
Arti Arya India
Imre Lendák Serbia
Leonard Bolc Poland
Arun Solanki India
Chuanqi Tao China
Li Fang Hu China
Shams Ul Arfeen Laghari Malaysia
M. Talib relative to Jedrzej Rybicki Germany Jedrzej Rybicki's profile →
Citations per field
00.5×2×4×6×8×9.3×
Jedrzej Rybicki · 1×
Citations per year

Countries citing papers authored by M. Talib

Since Specialization
Citations

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

Fields of papers citing papers by M. Talib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside M. Talib, 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. Talib Line = papers co-authored together M. Talib 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 202058
2 202148
3 202131
4 202128
5 202125
6 200621
7 202118
8 202118
9 202117
10 202114
11 202114
12 202013
13 202113
14 202011
15 202010
16 20217
17 20244
18
Improving the load balance for hybrid partitioning scheme by directing hybrid queries
20082
19 20062
20 20062

About M. Talib

M. Talib is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems, Artificial Intelligence and Computational Theory and Mathematics, having authored 25 papers that have together received 357 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (4 papers), Advanced Steganography and Watermarking Techniques (4 papers), IoT and Edge/Fog Computing (4 papers), Network Security and Intrusion Detection (4 papers), Blockchain Technology Applications and Security (3 papers), Opportunistic and Delay-Tolerant Networks (3 papers), Advanced Data and IoT Technologies (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Computer Networks and Communications (100 citations), Linguistics and Language (19 citations), Signal Processing (40 citations), Information Systems (79 citations) and Computer Vision and Pattern Recognition (68 citations). M. Talib has collaborated with scholars based in Malaysia, Papua New Guinea and India. Frequent co-authors include Noor Zaman Jhanjhi, Sahil Verma, Kavita Kavita, Aman Deep Singh, Mamoona Humayun, Varun Dogra, G. Suseendran, Muhammad Ibrahim Khalil, Thamer Tabbakh and Divya Anand. Their work appears in journals such as International Journal of Innovation Science, Scientific Reports, Journal of Discrete Mathematical Sciences and Cryptography, Indonesian Journal of Electrical Engineering and Computer Science and Lecture notes in networks and systems.

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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