V. Kalaichelvi
- Computer Vision and Pattern Recognition top 10%
- Mechanical Engineering
- Automotive Engineering top 10%
- Control and Systems Engineering top 10%
- Electrical and Electronic Engineering
- Co-authors
- R. KarthikeyanRaja MuthalaguD. SivakumarK. PalanikumarV. SrinivasanShazia HasanNilesh GoelG. Karthikeyan
- Topics
- Robotic Path Planning Algorithms (8 papers)Robot Manipulation and Learning (7 papers)Welding Techniques and Residual Stresses (7 papers)
- Cited by
- Automotive EngineeringComputer Vision and Pattern RecognitionIndustrial and Manufacturing Engineering
- Partner nations
- United Arab EmiratesIndiaUnited States
In The Last Decade
V. Kalaichelvi
41 papers receiving 299 citations
Peers
Comparison fields: 5 of 71
- Computer Vision and Pattern Recognition 106
- Mechanical Engineering 90
- Automotive Engineering 75
- Control and Systems Engineering 69
- Electrical and Electronic Engineering 43
Countries citing papers authored by V. Kalaichelvi
This map shows the geographic impact of V. Kalaichelvi'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 V. Kalaichelvi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. Kalaichelvi more than expected).
Fields of papers citing papers by V. Kalaichelvi
This network shows the impact of papers produced by V. Kalaichelvi. 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 V. Kalaichelvi. The network helps show where V. Kalaichelvi may publish in the future.
Co-authorship network of co-authors of V. Kalaichelvi
This figure shows the co-authorship network connecting the top 25 collaborators of V. Kalaichelvi. A scholar is included among the top collaborators of V. Kalaichelvi 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 V. Kalaichelvi. V. Kalaichelvi 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 | 5 | |
| 6 | 13 | |
| 7 | 7 | |
| 8 | 61 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | 6 | |
| 13 | 7 | |
| 14 | 1 | |
| 15 | 6 | |
| 16 | 3 | |
| 17 | 0 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 8 |
About V. Kalaichelvi
V. Kalaichelvi is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Industrial and Manufacturing Engineering, having authored 46 papers that have together received 314 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (8 papers), Robot Manipulation and Learning (7 papers) and Welding Techniques and Residual Stresses (7 papers). The work is most often cited by research in Automotive Engineering (75 citations), Computer Vision and Pattern Recognition (106 citations) and Industrial and Manufacturing Engineering (30 citations). V. Kalaichelvi has collaborated with scholars based in United Arab Emirates, India and United States. Frequent co-authors include R. Karthikeyan, Raja Muthalagu, D. Sivakumar, K. Palanikumar, V. Srinivasan, D. Sivakumar, Shazia Hasan, Nilesh Goel, G. Karthikeyan and Abhinav Pathak. Their work appears in journals such as IEEE Access, Applied Sciences 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.