Mohsin Ali Memon

34 papers receiving 257 citations

Peers

Mohsin Ali Memon
Comparison fields: 5 of 89
  • Human-Computer Interaction 19
  • Artificial Intelligence 96
  • Computer Vision and Pattern Recognition 49
  • Computer Networks and Communications 51
  • Signal Processing 23
Replace Sania Bhatti with:
Sania Bhatti Pakistan
Eoghan Furey United Kingdom
Sandro Rodriguez Garzon Germany
Hanif Fakhrurroja Indonesia
Malin Nilsson Sweden
Lucia Cascone Italy
Jiayang Wu China
Rolando Quintero Mexico
Quan Kong Japan
Achin Jain India
Mohsin Ali Memon relative to Sania Bhatti Pakistan Sania Bhatti's profile →
Citations per field
00.5×1.5×
Sania Bhatti · 1×
Citations per year

Countries citing papers authored by Mohsin Ali Memon

Since Specialization
Citations

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

Fields of papers citing papers by Mohsin Ali Memon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohsin Ali Memon. 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 Mohsin Ali Memon. The network helps show where Mohsin Ali Memon may publish in the future.

Co-authors

The 23 scholars most cited alongside Mohsin Ali Memon, 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 Mohsin Ali Memon Line = papers co-authored together Mohsin Ali Memon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202150
2 201138
3 201837
4 201920
5 202116
6 202315
7 202113
8 202011
9 201811
10 20205
11 20185
12 20174
13 20194
14 20174
15 20214
16 20104
17 20104
18
A Digital Diary: Remembering the Past Using the Present Context
20163
19 20123
20 20123

About Mohsin Ali Memon

Mohsin Ali Memon is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems and Media Technology, having authored 39 papers that have together received 275 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (5 papers), Opportunistic and Delay-Tolerant Networks (4 papers), Vehicle License Plate Recognition (3 papers), Hate Speech and Cyberbullying Detection (3 papers), Energy Efficient Wireless Sensor Networks (3 papers), Bullying, Victimization, and Aggression (3 papers), Facility Location and Emergency Management (2 papers) and Handwritten Text Recognition Techniques (2 papers). The work is most often cited by research in Human-Computer Interaction (19 citations), Artificial Intelligence (96 citations), Computer Vision and Pattern Recognition (49 citations), Computer Networks and Communications (51 citations) and Signal Processing (23 citations). Mohsin Ali Memon has collaborated with scholars based in Pakistan, Japan and United Kingdom. Frequent co-authors include Sania Bhatti, Jie Xu, Sheeraz Memon, Kyoung‐Sook Kim, Asadullah Shaikh, Hani Alshahrani, Adel Sulaiman, Jiro Tanaka, Abdullah Alghamdi and Mohammed Hamdi. Their work appears in journals such as Applied Sciences, Journal Of Big Data, IET Wireless Sensor Systems, International Journal of Information Technology and International Journal of Modern Education and Computer Science.

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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