Md. Monirul Islam
- Artificial Intelligence top 2%
- Electrical and Electronic Engineering
- Information Systems top 10%
- Accounting top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Kazuyuki MuraseSukarna BaruaXin YaoKazi Md. Rokibul AlamMd. Faijul AminMd. Golam Rabiul Alam
- Topics
- Fuzzy and Soft Set Theory (6 papers)Neural Networks and Applications (2 papers)Face and Expression Recognition (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Knowledge and Data EngineeringData in Brief
- Partner nations
- IndiaBangladeshUnited Kingdom
In The Last Decade
Md. Monirul Islam
12 papers receiving 826 citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 706
- Electrical and Electronic Engineering 304
- Information Systems 96
- Accounting 94
- Computer Vision and Pattern Recognition 88
Countries citing papers authored by Md. Monirul Islam
This map shows the geographic impact of Md. Monirul Islam'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. Monirul Islam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md. Monirul Islam more than expected).
Fields of papers citing papers by Md. Monirul Islam
This network shows the impact of papers produced by Md. Monirul Islam. 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. Monirul Islam. The network helps show where Md. Monirul Islam may publish in the future.
Co-authorship network of co-authors of Md. Monirul Islam
This figure shows the co-authorship network connecting the top 25 collaborators of Md. Monirul Islam. A scholar is included among the top collaborators of Md. Monirul Islam 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 Md. Monirul Islam. Md. Monirul Islam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learningbreakdown → | 828 |
| 12 | 6 | |
| 13 | 3 |
About Md. Monirul Islam
Md. Monirul Islam is a scholar working on Business and International Management, Management Science and Operations Research and Statistics and Probability, having authored 13 papers that have together received 861 indexed citations. Recurring topics across this work include Fuzzy and Soft Set Theory (6 papers), Neural Networks and Applications (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Artificial Intelligence (706 citations), Health Information Management (76 citations) and Software (32 citations). Md. Monirul Islam has collaborated with scholars based in India, Bangladesh and United Kingdom. Frequent co-authors include Kazuyuki Murase, Sukarna Barua, Xin Yao, Kazi Md. Rokibul Alam, Md. Faijul Amin and Md. Golam Rabiul Alam. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and Data in Brief.
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.