Subarna Tripathi

85 total papers · 943 total citations
20 papers, 304 citations indexed

About

Subarna Tripathi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Subarna Tripathi has authored 20 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Subarna Tripathi's work include Multimodal Machine Learning Applications (7 papers), Video Analysis and Summarization (5 papers) and Human Pose and Action Recognition (5 papers). Subarna Tripathi is often cited by papers focused on Multimodal Machine Learning Applications (7 papers), Video Analysis and Summarization (5 papers) and Human Pose and Action Recognition (5 papers). Subarna Tripathi collaborates with scholars based in United States, India and United Kingdom. Subarna Tripathi's co-authors include Truong Q. Nguyen, Byeongkeun Kang, Xiang Zhang, Zhuowen Tu, Brian Guenter, Xiaolong Wang, Shaowei Liu, Kien Nguyen, Tanaya Guha and Kyle Min and has published in prestigious journals such as IEEE Access, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Warwick Research Archive Portal (University of Warwick).

In The Last Decade

Subarna Tripathi

19 papers receiving 286 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Subarna Tripathi 226 95 72 46 35 20 304
G. K. Kharate 134 0.6× 103 1.1× 55 0.8× 45 1.0× 28 0.8× 43 266
Farhad Dadgostar 160 0.7× 95 1.0× 83 1.2× 55 1.2× 14 0.4× 25 307
Pradyumna Narayana 164 0.7× 136 1.4× 81 1.1× 27 0.6× 60 1.7× 18 254
Md. Sanzidul Islam 144 0.6× 79 0.8× 72 1.0× 55 1.2× 36 1.0× 25 340
Noramiza Hashim 113 0.5× 56 0.6× 60 0.8× 12 0.3× 27 0.8× 25 259
Charul Bhatnagar 227 1.0× 62 0.7× 71 1.0× 38 0.8× 39 1.1× 39 314
Shagan Sah 150 0.7× 42 0.4× 110 1.5× 19 0.4× 26 0.7× 23 333
Stephan Liwicki 265 1.2× 111 1.2× 57 0.8× 73 1.6× 44 1.3× 18 359
Byeongkeun Kang 180 0.8× 98 1.0× 24 0.3× 46 1.0× 42 1.2× 19 257
Gibran Benítez-García 184 0.8× 96 1.0× 29 0.4× 18 0.4× 39 1.1× 32 252

Countries citing papers authored by Subarna Tripathi

Since Specialization
Citations

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

Fields of papers citing papers by Subarna Tripathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Subarna Tripathi

This figure shows the co-authorship network connecting the top 25 collaborators of Subarna Tripathi. A scholar is included among the top collaborators of Subarna Tripathi 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 Subarna Tripathi. Subarna Tripathi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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