V. P. Singh
- Plant Science top 10%
- Genetics top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Snehashish ChakravertyAbhijit MukherjeeParteek KumarSatish KumarHarjeet SinghManinder SinghBrigitte CourtoisJiwan S. Sidhu
- Topics
- Natural Language Processing Techniques (11 papers)Topic Modeling (8 papers)Handwritten Text Recognition Techniques (8 papers)
- Partner nations
- IndiaAustraliaUnited States
In The Last Decade
V. P. Singh
50 papers receiving 663 citations
Peers
Comparison fields: 5 of 100
- Plant Science 242
- Genetics 182
- Artificial Intelligence 152
- Computer Vision and Pattern Recognition 95
- Computer Networks and Communications 82
Countries citing papers authored by V. P. Singh
This map shows the geographic impact of V. P. Singh'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. P. Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. P. Singh more than expected).
Fields of papers citing papers by V. P. Singh
This network shows the impact of papers produced by V. P. Singh. 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. P. Singh. The network helps show where V. P. Singh may publish in the future.
Co-authorship network of co-authors of V. P. Singh
This figure shows the co-authorship network connecting the top 25 collaborators of V. P. Singh. A scholar is included among the top collaborators of V. P. Singh 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. P. Singh. V. P. Singh 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 | 1 | |
| 3 | 9 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 7 | |
| 7 | 35 | |
| 8 | Object detection of colored images using improved point feature matching algorithm | 2 |
| 9 | 11 | |
| 10 | 15 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 10 | |
| 15 | A Review on Various Error Detection and Correction Methods Used in Communication | 12 |
| 16 | Quantum Neural Network based Parts of Speech Tagger for Hindi | 4 |
| 17 | 13 | |
| 18 | 14 | |
| 19 | 12 | |
| 20 | 228 |
About V. P. Singh
V. P. Singh is a scholar working on Ecological Modeling, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 50 papers that have together received 700 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (11 papers), Topic Modeling (8 papers) and Handwritten Text Recognition Techniques (8 papers). The work is most often cited by research in Ecological Modeling (39 citations), Plant Science (242 citations) and Genetics (182 citations). V. P. Singh has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Snehashish Chakraverty, Abhijit Mukherjee, Parteek Kumar, Satish Kumar, Harjeet Singh, Maninder Singh, Brigitte Courtois, Jiwan S. Sidhu, Jie‐Yun Zhuang and Yu-Ting Huang. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Theoretical and Applied Genetics and Wear.
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.