Padma Polash Paul
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Information Systems top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Co-authors
- Marina L. GavrilovaMadeena SultanaFaisal AhmedReda AlhajjYingxu WangStanislav KlimenkoPatrick S. P. WangYaoyao Fiona Zhao
- Topics
- Biometric Identification and Security (18 papers)Face recognition and analysis (16 papers)User Authentication and Security Systems (15 papers)
- Journals
- Journal of Thrombosis and HaemostasisIEEE Transactions on Systems Man and Cybernetics SystemsComputers in Industry
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Padma Polash Paul
42 papers receiving 540 citations
Peers
Comparison fields: 5 of 79
- Computer Vision and Pattern Recognition 339
- Signal Processing 244
- Information Systems 207
- Artificial Intelligence 116
- Biomedical Engineering 104
Countries citing papers authored by Padma Polash Paul
This map shows the geographic impact of Padma Polash Paul'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 Padma Polash Paul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Padma Polash Paul more than expected).
Fields of papers citing papers by Padma Polash Paul
This network shows the impact of papers produced by Padma Polash Paul. 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 Padma Polash Paul. The network helps show where Padma Polash Paul may publish in the future.
Co-authorship network of co-authors of Padma Polash Paul
This figure shows the co-authorship network connecting the top 25 collaborators of Padma Polash Paul. A scholar is included among the top collaborators of Padma Polash Paul 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 Padma Polash Paul. Padma Polash Paul is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 5 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 38 | |
| 6 | Identifying Users from Online Interactions in Twitter. | 1 |
| 7 | 1 | |
| 8 | Kinect-based gait recognition using sequences of the most relevant joint relative angles | 23 |
| 9 | 4 | |
| 10 | 29 | |
| 11 | 3 | |
| 12 | 14 | |
| 13 | 5 | |
| 14 | 31 | |
| 15 | 53 | |
| 16 | 2 | |
| 17 | 17 | |
| 18 | 6 | |
| 19 | 16 | |
| 20 | 6 |
About Padma Polash Paul
Padma Polash Paul is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Information Systems, having authored 42 papers that have together received 563 indexed citations. Recurring topics across this work include Biometric Identification and Security (18 papers), Face recognition and analysis (16 papers) and User Authentication and Security Systems (15 papers). The work is most often cited by research in Signal Processing (244 citations), Computer Vision and Pattern Recognition (339 citations) and Human-Computer Interaction (59 citations). Padma Polash Paul has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Marina L. Gavrilova, Madeena Sultana, Faisal Ahmed, Reda Alhajj, Yingxu Wang, Stanislav Klimenko, Patrick S. P. Wang, Yaoyao Fiona Zhao, Md. Rabiul Islam and Sumita Danda. Their work appears in journals such as Journal of Thrombosis and Haemostasis, IEEE Transactions on Systems Man and Cybernetics Systems and Computers in Industry.
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.