Bharath Ramesh

951 citations
59 papers · 574 · h-index 14

Impact in

Papers in

Bharath Ramesh

52 papers receiving 526 citations

Peers

Bharath Ramesh
Comparison fields: 5 of 74
  • Computer Vision and Pattern Recognition 266
  • Media Technology 86
  • Artificial Intelligence 110
  • Cognitive Neuroscience 58
  • Electrical and Electronic Engineering 177
Replace Ik Hyun Lee with:
Ik Hyun Lee South Korea
Yongjian Deng China
Wei Xing China
Paul Watta United States
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Citations per field
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Citations per year

Countries citing papers authored by Bharath Ramesh

Since Specialization
Citations

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

Fields of papers citing papers by Bharath Ramesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bharath Ramesh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bharath Ramesh Line = papers co-authored together Bharath Ramesh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201969
2 201962
3 201442
4 202040
5 201934
6 201733
7 201725
8
Long-term object tracking with a moving event camera.
201818
9 201917
10 202516
11 201614
12 202114
13 201914
14 202013
15 202013
16 202211
17 202311
18 200810
19 20218
20 20178

About Bharath Ramesh

Bharath Ramesh is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 59 papers that have together received 574 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (10 papers), Advanced Memory and Neural Computing (9 papers), Advanced Vision and Imaging (8 papers), Mobile Ad Hoc Networks (7 papers), Advanced Neural Network Applications (6 papers), Video Surveillance and Tracking Methods (5 papers), Face and Expression Recognition (4 papers) and Wireless Networks and Protocols (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (266 citations), Media Technology (86 citations), Artificial Intelligence (110 citations), Cognitive Neuroscience (58 citations) and Electrical and Electronic Engineering (177 citations). Bharath Ramesh has collaborated with scholars based in Singapore, United States and India. Frequent co-authors include Cheng Xiang, Zhi Gao, Hong Yang, Garrick Orchard, Hong Ji, Tong Heng Lee, Simona Siri, Jinqiang Cui, Yue Yang and H L Gururaj. Their work appears in journals such as Frontiers in Neuroscience, Pattern Recognition, Sensors, Neurocomputing and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

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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