S. Vimal
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Health Information Management top 1%
- Computer Vision and Pattern Recognition top 5%
- Plant Science
- Co-authors
- M. KaliappanMi Young LeeHarold RobinsonGaurav DhimanAshutosh SharmaAmandeep KaurDiego OlivaKrishna Kant Singh
- Topics
- Smart Agriculture and AI (6 papers)Artificial Intelligence in Healthcare (5 papers)COVID-19 diagnosis using AI (5 papers)
- Cited by
- Health Information ManagementArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Internet of Things Journal
- Partner nations
- IndiaSouth KoreaAustralia
In The Last Decade
S. Vimal
58 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 145
- Artificial Intelligence 376
- Computer Networks and Communications 163
- Health Information Management 158
- Computer Vision and Pattern Recognition 157
- Plant Science 136
Countries citing papers authored by S. Vimal
This map shows the geographic impact of S. Vimal'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 S. Vimal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Vimal more than expected).
Fields of papers citing papers by S. Vimal
This network shows the impact of papers produced by S. Vimal. 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 S. Vimal. The network helps show where S. Vimal may publish in the future.
Co-authorship network of co-authors of S. Vimal
This figure shows the co-authorship network connecting the top 25 collaborators of S. Vimal. A scholar is included among the top collaborators of S. Vimal 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 S. Vimal. S. Vimal 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 | 3 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 43 | |
| 8 | 5 | |
| 9 | 9 | |
| 10 | 0 | |
| 11 | 8 | |
| 12 | 18 | |
| 13 | 18 | |
| 14 | IoT Based Smart Health Monitoring with CNN Using Edge Computing | 28 |
| 15 | REDUCING LATENCY IN SMART MANUFACTURING SERVICE SYSTEM USING EDGE COMPUTING | 2 |
| 16 | 29 | |
| 17 | 21 | |
| 18 | Word and graph embeddings for covid-19 retweet prediction | 1 |
| 19 | 77 | |
| 20 | 18 |
About S. Vimal
S. Vimal is a scholar working on Health Information Management, Health Informatics and Computer Vision and Pattern Recognition, having authored 68 papers that have together received 1.2k indexed citations. Recurring topics across this work include Smart Agriculture and AI (6 papers), Artificial Intelligence in Healthcare (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Information Management (158 citations), Artificial Intelligence (376 citations) and Computer Vision and Pattern Recognition (157 citations). S. Vimal has collaborated with scholars based in India, South Korea and Australia. Frequent co-authors include M. Kaliappan, Mi Young Lee, Harold Robinson, Gaurav Dhiman, Ashutosh Sharma, Amandeep Kaur, Diego Oliva, Krishna Kant Singh, Korhan Cengiz and E. Golden Julie. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Internet of Things Journal.
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.