R. Krishnamoorthy

440 total citations
46 papers, 294 citations indexed

About

R. Krishnamoorthy is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, R. Krishnamoorthy has authored 46 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 8 papers in Information Systems. Recurrent topics in R. Krishnamoorthy's work include Advanced Data Compression Techniques (10 papers), Image and Signal Denoising Methods (8 papers) and Data Mining Algorithms and Applications (6 papers). R. Krishnamoorthy is often cited by papers focused on Advanced Data Compression Techniques (10 papers), Image and Signal Denoising Methods (8 papers) and Data Mining Algorithms and Applications (6 papers). R. Krishnamoorthy collaborates with scholars based in India, Malaysia and Norway. R. Krishnamoorthy's co-authors include Mohamed Saiyad Musthafa, K. Udhayakumar, Raju Kannadasan, Lucian Mihet‐Popa, Rajvikram Madurai Elavarasan, P. Murali, A. Kannan, T. Karthikeyan, D. Manjula and K. Somasundaram and has published in prestigious journals such as SHILAP Revista de lepidopterología, Energies and Signal Processing.

In The Last Decade

R. Krishnamoorthy

39 papers receiving 264 citations

Peers

R. Krishnamoorthy
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 71
  • Information Systems 64
  • Artificial Intelligence 46
  • Radiological and Ultrasound Technology 42
  • Electrical and Electronic Engineering 37
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Citations per field, relative to R. Krishnamoorthy
R. Krishnamoorthy · 1×
Citations per year, relative to R. Krishnamoorthy
R. Krishnamoorthy · 1×

Countries citing papers authored by R. Krishnamoorthy

Since Specialization
Citations

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

Fields of papers citing papers by R. Krishnamoorthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Krishnamoorthy

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 5
2 1
3 53
4 2
5 5
6 3
7 3
8 4
9 0
10 3
11 2
12 2
13 0
14 1
15 43
16 6
17 1
18
Performance evaluation of the software visualization tools and a new framework to manage cognitive load in computer program learning
2
19
Nodulation and Yield of Mungbean { Vigna radiata (L.)} Influenced by Integrated Weed Management Practices
17
20
Response of Weed Management Practices on the Growth and Yield of Urdbean { Vigna mungo L. Hepper}
2

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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