Gajula Ramesh

417 citations
40 papers · 156 · h-index 6

Impact in

Papers in

Gajula Ramesh

28 papers receiving 127 citations

Peers

Gajula Ramesh
Comparison fields: 5 of 64
  • Computer Vision and Pattern Recognition 39
  • Artificial Intelligence 45
  • Signal Processing 15
  • Media Technology 9
  • Health Information Management 4
Replace S Abhishek with:
S Abhishek India
Annajiat Alim Rasel Bangladesh
Shaikh Muhammad Allayear Bangladesh
Rashmita Khilar India
P. Pandiaraja India
B. Paulchamy India
Bhawani Sankar Panigrahi India
Aman Chadha United States
Jian Pei United States
Humza Naveed Pakistan
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Citations per field
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Citations per year

Countries citing papers authored by Gajula Ramesh

Since Specialization
Citations

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

Fields of papers citing papers by Gajula Ramesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Gajula 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 Gajula Ramesh Line = papers co-authored together Gajula Ramesh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202039
2 201926
3 202318
4 20236
5 20196
6
Summarizing Product Reviews Using NLP Based Text Summarization
20195
7 20245
8 20175
9 20225
10 20214
11 20214
12 20234
13 20232
14 20232
15 20202
16 20212
17 20242
18 20102
19 20052
20 20032

About Gajula Ramesh

Gajula Ramesh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 40 papers that have together received 156 indexed citations. Recurring topics across this work include Smart Agriculture and AI (5 papers), Blockchain Technology Applications and Security (3 papers), Advanced Neural Network Applications (3 papers), IoT and Edge/Fog Computing (3 papers), Remote Sensing in Agriculture (3 papers), Topic Modeling (3 papers), Advanced Photonic Communication Systems (3 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (39 citations), Artificial Intelligence (45 citations), Signal Processing (15 citations), Media Technology (9 citations) and Health Information Management (4 citations). Gajula Ramesh has collaborated with scholars based in India, Iraq and Malaysia. Frequent co-authors include Anil Kumar Budati, Louai A. Maghrabi, S. Kumaravel, N. Srinivasa, Jose Anand, Gandikota Ramu, Mohammad Kamrul Hasan, Neeraj Varshney, K. Reddy Madhavi and Hassan Ali. Their work appears in journals such as Indian Journal of Pharmaceutical Education and Research, Multimedia Tools and Applications, Tsinghua Science & Technology, Applied Nanoscience and Spatial Information Research.

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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