Manjeevan Seera
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 1%
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Neural Networks and Applications
Papers in
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- Neural Networks and Applications 10
- Fuzzy Logic and Control Systems 10
- Machine Learning and ELM 5
- Imbalanced Data Classification Techniques 5
- Data Stream Mining Techniques 5
- Co-authors
- Chee Peng Lim (25 shared papers)Chu Kiong Loo (28 shared papers)Asoke K. Nandi (3 shared papers)Dahaman Ishak (3 shared papers)Harbindar Jeet Singh (1 shared paper)Saeid Nahavandi (1 shared paper)Lakhmi C. Jain (1 shared paper)P. Balasubramaniam (1 shared paper)
In The Last Decade
Manjeevan Seera
58 papers receiving 1.6k citations
Manjeevan Seera's Hit Papers
Peers
Comparison fields: 5 of 128
- Health Information Management 165
- Artificial Intelligence 889
- Control and Systems Engineering 459
- Accounting 163
- Media Technology 102
Countries citing papers authored by Manjeevan Seera
This map shows the geographic impact of Manjeevan Seera'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 Manjeevan Seera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manjeevan Seera more than expected).
Fields of papers citing papers by Manjeevan Seera
This network shows the impact of papers produced by Manjeevan Seera. 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 Manjeevan Seera. The network helps show where Manjeevan Seera may publish in the future.
Co-authors
The 25 scholars most cited alongside Manjeevan Seera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Credit Card Fraud Detection Using AdaBoost and Majority Voting Hit paper breakdown → | 2018 | 288 |
| 2 | 2013 | 216 | |
| 3 | 2011 | 140 | |
| 4 | 2014 | 103 | |
| 5 | 2021 | 80 | |
| 6 | 2013 | 79 | |
| 7 | 2013 | 59 | |
| 8 | 2017 | 57 | |
| 9 | 2019 | 49 | |
| 10 | 2013 | 40 | |
| 11 | 2014 | 37 | |
| 12 | 2021 | 34 | |
| 13 | 2017 | 33 | |
| 14 | 2014 | 32 | |
| 15 | 2014 | 32 | |
| 16 | 2012 | 24 | |
| 17 | 2015 | 22 | |
| 18 | 2019 | 22 | |
| 19 | 2015 | 22 | |
| 20 | 2017 | 21 |
About Manjeevan Seera
Manjeevan Seera is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Electrical and Electronic Engineering and Molecular Biology, having authored 58 papers that have together received 1.7k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (10 papers), Neural Networks and Applications (10 papers), Fuzzy Logic and Control Systems (10 papers), Fault Detection and Control Systems (9 papers), Machine Learning and ELM (5 papers), Imbalanced Data Classification Techniques (5 papers), Data Stream Mining Techniques (5 papers) and Emotion and Mood Recognition (4 papers). The work is most often cited by research in Health Information Management (165 citations), Artificial Intelligence (889 citations), Control and Systems Engineering (459 citations), Accounting (163 citations) and Media Technology (102 citations). Manjeevan Seera has collaborated with scholars based in Malaysia, Australia and Japan. Frequent co-authors include Chee Peng Lim, Chu Kiong Loo, Asoke K. Nandi, Dahaman Ishak, Harbindar Jeet Singh, Saeid Nahavandi, Lakhmi C. Jain, P. Balasubramaniam, M. L. Dennis Wong and Lalitha Dhamotharan. Their work appears in journals such as Applied Soft Computing, Neural Computing and Applications, IEEE Access, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.
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.