Urmish Thakker

About

Urmish Thakker is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Urmish Thakker has authored 5 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Electrical and Electronic Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Urmish Thakker’s work include Advanced Neural Network Applications (2 papers), Machine Learning and ELM (1 paper) and CCD and CMOS Imaging Sensors (1 paper). Urmish Thakker is often cited by papers focused on Advanced Neural Network Applications (2 papers), Machine Learning and ELM (1 paper) and CCD and CMOS Imaging Sensors (1 paper). Urmish Thakker collaborates with scholars based in United States. Urmish Thakker's co-authors include Shiqiang Wang, Ahmed Imteaj, M. Hadi Amini, Jian Li, Matthew Mattina, Ganesh Dasika and Igor Fedorov and has published in prestigious journals such as IEEE Internet of Things Journal, ACM Journal on Emerging Technologies in Computing Systems and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of Urmish Thakker i

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Fields of papers citing papers by Urmish Thakker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Urmish Thakker. 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 Urmish Thakker. The network helps show where Urmish Thakker may publish in the future.

Countries citing papers authored by Urmish Thakker

Since Specialization

Citations

This map shows the geographic impact of Urmish Thakker'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 Urmish Thakker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Urmish Thakker 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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