Vinod K Kurmi

19 papers and 252 indexed citations i.

About

Vinod K Kurmi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Vinod K Kurmi has authored 19 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Vinod K Kurmi’s work include Domain Adaptation and Few-Shot Learning (10 papers), Multimodal Machine Learning Applications (7 papers) and COVID-19 diagnosis using AI (4 papers). Vinod K Kurmi is often cited by papers focused on Domain Adaptation and Few-Shot Learning (10 papers), Multimodal Machine Learning Applications (7 papers) and COVID-19 diagnosis using AI (4 papers). Vinod K Kurmi collaborates with scholars based in India, United Kingdom and United States. Vinod K Kurmi's co-authors include Vinay P. Namboodiri, Venkatesh K. Subramanian, Shanu Kumar, Badri N. Patro, Sandeep Kumar, K. S. Venkatesh, Yong‐Sheng Chen, Prem Kalra, Antitza Dantcheva and Sandeep Kumar and has published in prestigious journals such as Neurocomputing, Image and Vision Computing and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Co-authorship network of co-authors of Vinod K Kurmi i

Fields of papers citing papers by Vinod K Kurmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vinod K Kurmi. 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 Vinod K Kurmi. The network helps show where Vinod K Kurmi may publish in the future.

Countries citing papers authored by Vinod K Kurmi

Since Specialization
Citations

This map shows the geographic impact of Vinod K Kurmi'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 Vinod K Kurmi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vinod K Kurmi more than expected).

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.

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