Mohd. Asyraf Mansor

81 papers receiving 1.0k citations

Peers

Mohd. Asyraf Mansor
Comparison fields: 5 of 80
  • Artificial Intelligence 785
  • Computer Vision and Pattern Recognition 230
  • Information Systems 153
  • Electrical and Electronic Engineering 150
  • Computational Theory and Mathematics 130
Replace Mohd Shareduwan Mohd Kasihmuddin with:
Mohd Shareduwan Mohd Kasihmuddin Malaysia
Saratha Sathasivam Malaysia
Prakash Shelokar India
Yuanxiang Li China
Dantong Ouyang China
Hossein Ebrahimpour-Komleh Iran
Bin Gu China
Avinash Chandra Pandey India
Qidi Wu China
Mohammad A. Hassonah Jordan
Mohd. Asyraf Mansor relative to Mohd Shareduwan Mohd Kasihmuddin Malaysia Mohd Shareduwan Mohd Kasihmuddin's profile →
Citations per field
00.5×1.5×
Mohd Shareduwan Mohd Kasihmuddin · 1×
Citations per year

Countries citing papers authored by Mohd. Asyraf Mansor

Since Specialization
Citations

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

Fields of papers citing papers by Mohd. Asyraf Mansor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohd. Asyraf Mansor. 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 Mohd. Asyraf Mansor. The network helps show where Mohd. Asyraf Mansor may publish in the future.

Co-authorship network of co-authors of Mohd. Asyraf Mansor

This figure shows the co-authorship network connecting the top 25 collaborators of Mohd. Asyraf Mansor. A scholar is included among the top collaborators of Mohd. Asyraf Mansor 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 Mohd. Asyraf Mansor. Mohd. Asyraf Mansor 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 1
2 4
3 0
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5 0
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7 0
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10 6
11 17
12 51
13 14
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15 24
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18 36
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Maximum 2-satisfiability in radial basis function neural network
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20 4

About Mohd. Asyraf Mansor

Mohd. Asyraf Mansor is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 89 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural Networks and Applications (61 papers), Fuzzy Logic and Control Systems (32 papers) and Rough Sets and Fuzzy Logic (13 papers). The work is most often cited by research in Artificial Intelligence (785 citations), Computer Vision and Pattern Recognition (230 citations) and Computational Theory and Mathematics (130 citations). Mohd. Asyraf Mansor has collaborated with scholars based in Malaysia, China and Bangladesh. Frequent co-authors include Mohd Shareduwan Mohd Kasihmuddin, Saratha Sathasivam, Nur Ezlin Zamri, Siti Zulaikha Mohd Jamaludin, Md Faisal Md Basir, Habibah A. Wahab, Mustafa Mamat, Siti Maisharah Sheikh Ghadzi, Ahmad Izani Md. Ismail and Aslina Baharum. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Applied Soft Computing.

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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