Shilpa Sethi
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Biomedical Engineering
- Human-Computer Interaction top 10%
- Co-authors
- Mamta KathuriaTanveer Syeda-MahmoodRahul UpadhyayHari SinghVishal GuptaVivek Ranjan SinhaBiplab MishraAnukrati Sharma
- Topics
- Web Data Mining and Analysis (5 papers)Recommender Systems and Techniques (4 papers)Data Management and Algorithms (4 papers)
- Partner nations
- IndiaCanadaUnited States
In The Last Decade
Shilpa Sethi
17 papers receiving 248 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 175
- Artificial Intelligence 46
- Radiology, Nuclear Medicine and Imaging 43
- Biomedical Engineering 40
- Human-Computer Interaction 31
Countries citing papers authored by Shilpa Sethi
This map shows the geographic impact of Shilpa Sethi'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 Shilpa Sethi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shilpa Sethi more than expected).
Fields of papers citing papers by Shilpa Sethi
This network shows the impact of papers produced by Shilpa Sethi. 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 Shilpa Sethi. The network helps show where Shilpa Sethi may publish in the future.
Co-authorship network of co-authors of Shilpa Sethi
This figure shows the co-authorship network connecting the top 25 collaborators of Shilpa Sethi. A scholar is included among the top collaborators of Shilpa Sethi 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 Shilpa Sethi. Shilpa Sethi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 7 | |
| 6 | 122 | |
| 7 | 4 | |
| 8 | 9 | |
| 9 | 1 | |
| 10 | 19 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | 3 | |
| 14 | An efficient personalized query suggestion technique for providing relevant results | 1 |
| 15 | 1 | |
| 16 | Design of personalised search system based on user interest and query structuring | 4 |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 74 |
About Shilpa Sethi
Shilpa Sethi is a scholar working on Signal Processing, Information Systems and Health Information Management, having authored 19 papers that have together received 259 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (5 papers), Recommender Systems and Techniques (4 papers) and Data Management and Algorithms (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (175 citations), Human-Computer Interaction (31 citations) and Health Informatics (4 citations). Shilpa Sethi has collaborated with scholars based in India, Canada and United States. Frequent co-authors include Mamta Kathuria, Tanveer Syeda-Mahmood, Rahul Upadhyay, Hari Singh, Vishal Gupta, Vivek Ranjan Sinha, Biplab Mishra, Anukrati Sharma, Priyanka Rawat and Jyotindra Narayan. Their work appears in journals such as Sensors, Journal of Biomedical Informatics and Multimedia Tools and Applications.
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.