Yogendra Narayan

26 papers receiving 268 citations

Peers

Yogendra Narayan
Comparison fields: 5 of 80
  • Human-Computer Interaction 43
  • Cognitive Neuroscience 98
  • Biomedical Engineering 100
  • Ceramics and Composites 11
  • Rehabilitation 12
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Steve C. Chiu United States
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Xueli Sun China
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Citations per field
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Citations per year

Countries citing papers authored by Yogendra Narayan

Since Specialization
Citations

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

Fields of papers citing papers by Yogendra Narayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202034
2 202032
3 202030
4 201826
5 199923
6 201621
7 200219
8 201518
9 201518
10 202117
11 202212
12 20229
13 20218
14 20025
15 20164
16 20213
17
MI based Brain Signals identification using KNN and MLP Classifiers
20212
18 20212
19 20222
20
A comparative analysis for Haar wavelet efficiency to remove Gaussian and Speckle noise from image
20162

About Yogendra Narayan

Yogendra Narayan is a scholar working on Cognitive Neuroscience, Biomedical Engineering, Artificial Intelligence, Human-Computer Interaction and Electrical and Electronic Engineering, having authored 36 papers that have together received 294 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (16 papers), Muscle activation and electromyography studies (9 papers), Gaze Tracking and Assistive Technology (5 papers), Neuroscience and Neural Engineering (4 papers), Brain Tumor Detection and Classification (4 papers), Advanced Computing and Algorithms (3 papers), Electrical and Thermal Properties of Materials (3 papers) and Robot Manipulation and Learning (2 papers). The work is most often cited by research in Human-Computer Interaction (43 citations), Cognitive Neuroscience (98 citations), Biomedical Engineering (100 citations), Ceramics and Composites (11 citations) and Rehabilitation (12 citations). Yogendra Narayan has collaborated with scholars based in India, Saudi Arabia and Spain. Frequent co-authors include Lini Mathew, S. Chatterji, Aditya Bhardwaj, Preeti Kumari, V. Pendrick, Aly E. Fathy, Vineet Kumar Singh, Meet Kumari, Vivek Arya and Carlos Quiterio Gómez Muñoz. Their work appears in journals such as Archives of Computational Methods in Engineering, Energies, Transactions on Emerging Telecommunications Technologies, Journal of Intelligent & Fuzzy Systems and Multimedia Tools and Applications.

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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