Vrushali Kulkarni
About
In The Last Decade
Vrushali Kulkarni
35 papers receiving 502 citations
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 187
- Information Systems 156
- Computer Networks and Communications 110
- Signal Processing 89
- Computer Vision and Pattern Recognition 78
Countries citing papers authored by Vrushali Kulkarni
This map shows the geographic impact of Vrushali Kulkarni'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 Vrushali Kulkarni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vrushali Kulkarni more than expected).
Fields of papers citing papers by Vrushali Kulkarni
This network shows the impact of papers produced by Vrushali Kulkarni. 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 Vrushali Kulkarni. The network helps show where Vrushali Kulkarni may publish in the future.
Co-authorship network of co-authors of Vrushali Kulkarni
This figure shows the co-authorship network connecting the top 25 collaborators of Vrushali Kulkarni. A scholar is included among the top collaborators of Vrushali Kulkarni 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 Vrushali Kulkarni. Vrushali Kulkarni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | Automated estimation of grape ripeness | 4 |
| 9 | 30 | |
| 10 | 23 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 12 | |
| 15 | 1 | |
| 16 | 31 | |
| 17 | Effective Learning and Classification using Random Forest Algorithm | 32 |
| 18 | 9 | |
| 19 | Techniques for Traffic Sign Classification using Machine Learning- A Survey | 2 |
| 20 | Cerebral blood flow in Alzheimer's disease imaged by Positron Emission Tomography: the effects of physostigmine infusion | 5 |
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.