U. C. Niranjan

712 citations
28 papers · 471 · h-index 11

Impact in

Papers in

U. C. Niranjan

25 papers receiving 423 citations

Peers

U. C. Niranjan
Comparison fields: 5 of 57
  • Computer Vision and Pattern Recognition 272
  • Signal Processing 70
  • Cognitive Neuroscience 108
  • Cardiology and Cardiovascular Medicine 100
  • Computer Graphics and Computer-Aided Design 5
Replace Majid Komeili with:
Majid Komeili Canada
Xingjun Wang China
Yu Yin China
Adam Page United States
Yuxiang Xie China
C. S. Sastry India
Yaomin Wang China
S. Edward Jero India
Dhiah Al‐Shammary Iraq
Mithilesh Atulkar India
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Citations per field
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Citations per year

Countries citing papers authored by U. C. Niranjan

Since Specialization
Citations

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

Fields of papers citing papers by U. C. Niranjan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by U. C. Niranjan. 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 U. C. Niranjan. The network helps show where U. C. Niranjan may publish in the future.

Co-authors

The 25 scholars most cited alongside U. C. Niranjan, 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 U. C. Niranjan Line = papers co-authored together U. C. Niranjan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200279
2 200178
3 200465
4 199232
5 201731
6 200330
7 201525
8 200725
9 200518
10 201517
11 201315
12 19939
13 20028
14
An Efficient System Based On Closed Sequential Patterns for Web Recommendations
20107
15 20106
16
Independent Component Analysis of Electroencephalogram
20066
17 20024
18 20143
19 20043
20 20052

About U. C. Niranjan

U. C. Niranjan is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Signal Processing and Information Systems, having authored 28 papers that have together received 471 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (7 papers), ECG Monitoring and Analysis (7 papers), Blind Source Separation Techniques (5 papers), Advanced Steganography and Watermarking Techniques (4 papers), Image Retrieval and Classification Techniques (4 papers), Data Mining Algorithms and Applications (3 papers), Chaos-based Image/Signal Encryption (3 papers) and Heart Rate Variability and Autonomic Control (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (272 citations), Signal Processing (70 citations), Cognitive Neuroscience (108 citations), Cardiology and Cardiovascular Medicine (100 citations) and Computer Graphics and Computer-Aided Design (5 citations). U. C. Niranjan has collaborated with scholars based in India, Singapore and United States. Frequent co-authors include Darpan Anand, U. Rajendra Acharya, P. Subbanna Bhat, I.S.N. Murthy, Debaditya Acharya, G. Muralidhar Bairy, Subha D. Puthankattil, S. Sitharama Iyengar, Lim Choo Min and N. Kannathal. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Signal Processing, Computers in Biology and Medicine, Journal of Medical Systems and Medical & Biological Engineering & Computing.

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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