Monika Agarwal
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- Fault Detection and Control Systems 16
- Advanced Control Systems Optimization 11
- Control Systems and Identification 6
- Vibration and Dynamic Analysis 2
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- Image Enhancement Techniques 5
- Advanced Image Processing Techniques 3
- Artificial Intelligence top 10%
- Neural Networks and Applications 9
- Media Technology top 10%
- Advanced Image Fusion Techniques 4
- Co-authors
- Rashima MahajanMarcio de QueirozD.M. DawsonD.W.T. RippinDavid I. WilsonF. ZhangJonas SjöbergGeeta Rani
- Journals
- Automatica (1 paper)IEEE Transactions on Control Systems Technology (1 paper)IEEE Transactions on Robotics and Automation (1 paper)
- Partner nations
- SwitzerlandIndiaUnited States
In The Last Decade
Monika Agarwal
33 papers receiving 678 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Control and Systems Engineering 444
- Neurology 55
- Computer Vision and Pattern Recognition 126
- Artificial Intelligence 180
- Media Technology 42
Countries citing papers authored by Monika Agarwal
This map shows the geographic impact of Monika Agarwal'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 Monika Agarwal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monika Agarwal more than expected).
Fields of papers citing papers by Monika Agarwal
This network shows the impact of papers produced by Monika Agarwal. 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 Monika Agarwal. The network helps show where Monika Agarwal may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Monika Agarwal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 2 | |
| 3 | Deep learning for enhanced brain Tumor Detection and classificationbreakdown → | 2024 | 54 |
| 4 | 2020 | 4 | |
| 5 | 2020 | 19 | |
| 6 | 2018 | 1 | |
| 7 | 2017 | 24 | |
| 8 | Review of Matrix Decomposition Techniques for Signal Processing Applications | 2014 | 10 |
| 9 | 2013 | 9 | |
| 10 | 2002 | 39 | |
| 11 | 2002 | 4 | |
| 12 | 1998 | 85 | |
| 13 | 1997 | 19 | |
| 14 | 1997 | 94 | |
| 15 | 1993 | 3 | |
| 16 | Using a-priori information in networks | 1991 | 7 |
| 17 | 1989 | 17 | |
| 18 | 1988 | 6 | |
| 19 | On-Line Estimation of Time Delay and Continuous-Time Process Parameters | 1985 | 1 |
| 20 | 1985 | 8 |
About Monika Agarwal
Monika Agarwal is a scholar working on Control and Systems Engineering, Media Technology and Artificial Intelligence, having authored 34 papers that have together received 721 indexed citations. Recurring topics across this work include Fault Detection and Control Systems (16 papers), Advanced Control Systems Optimization (11 papers), Neural Networks and Applications (9 papers), Control Systems and Identification (6 papers), Image Enhancement Techniques (5 papers), Advanced Image Fusion Techniques (4 papers), Advanced Image Processing Techniques (3 papers) and Vibration and Dynamic Analysis (2 papers). The work is most often cited by research in Control and Systems Engineering (444 citations), Neurology (55 citations) and Computer Vision and Pattern Recognition (126 citations). Monika Agarwal has collaborated with scholars based in Switzerland, India and United States. Frequent co-authors include Rashima Mahajan, Marcio de Queiroz, D.M. Dawson, D.W.T. Rippin, David I. Wilson, F. Zhang, Jonas Sjöberg, Geeta Rani, Peter Terwiesch and Dominique Bonvin. Their work appears in journals such as Automatica, IEEE Transactions on Control Systems Technology and IEEE Transactions on Robotics and Automation.
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.