Md Munirul Haque

43 papers receiving 617 citations

Peers

Md Munirul Haque
Comparison fields: 5 of 103
  • Information Systems 165
  • Computer Networks and Communications 154
  • Information Systems and Management 33
  • Human-Computer Interaction 26
  • Computer Vision and Pattern Recognition 91
Replace Álvaro Alesanco with:
Álvaro Alesanco Spain
Randi Karlsen Norway
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David E. Kanter United States
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Citations per year

Countries citing papers authored by Md Munirul Haque

Since Specialization
Citations

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

Fields of papers citing papers by Md Munirul Haque

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Md Munirul Haque. 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 Md Munirul Haque. The network helps show where Md Munirul Haque may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200971
2 202054
3 199439
4 200739
5 200635
6 201433
7 200927
8 201726
9
SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.
201824
10 202124
11 202123
12 200722
13 201420
14 201520
15 201318
16 201815
17 201413
18 201413
19 201912
20 202011

About Md Munirul Haque

Md Munirul Haque is a scholar working on Information Systems, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 47 papers that have together received 648 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (6 papers), Autism Spectrum Disorder Research (6 papers), Opportunistic and Delay-Tolerant Networks (5 papers), Access Control and Trust (5 papers), User Authentication and Security Systems (5 papers), Cloud Data Security Solutions (5 papers), Cryptography and Data Security (5 papers) and ICT in Developing Communities (5 papers). The work is most often cited by research in Information Systems (165 citations), Computer Networks and Communications (154 citations), Information Systems and Management (33 citations), Human-Computer Interaction (26 citations) and Computer Vision and Pattern Recognition (91 citations). Md Munirul Haque has collaborated with scholars based in United States, Bangladesh and Canada. Frequent co-authors include Sheikh Iqbal Ahamed, Ragib Hasan, Shams Zawoad, Rasib Hassan Khan, Young L. Kim, Rohit Kulkarni, Shahid Noor, John MacDermot, Gabriel Olmos and Richard Reed Love. Their work appears in journals such as IEEE Transactions on Emerging Topics in Computing, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Optica, PLoS ONE and IEEE Transactions on Electron Devices.

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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