Vipul Narayan

28 papers receiving 753 citations

Vipul Narayan's Hit Papers

A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities 2023 · 168 citations
1680+1+2Years since publication50100150

Peers

Vipul Narayan
Comparison fields: 5 of 111
  • Health Information Management 74
  • Health Informatics 23
  • Computer Networks and Communications 296
  • Computer Vision and Pattern Recognition 123
  • Neurology 36
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Citations per year

Countries citing papers authored by Vipul Narayan

Since Specialization
Citations

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

Fields of papers citing papers by Vipul Narayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities
Hit paper breakdown →
2023168
2
A comparative assessment of artificial intelligence models used for early prediction and evaluation of chronic kidney disease
Hit paper breakdown →
2023103
3 199993
4 202351
5 202338
6 202134
7 202228
8 202326
9 202226
10 202226
11 202325
12 202422
13 202021
14 202318
15 202117
16 202015
17 202015
18 202213
19 202312
20 202010

About Vipul Narayan

Vipul Narayan is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Information Systems and Management Information Systems, having authored 34 papers that have together received 819 indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (15 papers), IoT-based Smart Home Systems (7 papers), Security in Wireless Sensor Networks (5 papers), Energy Harvesting in Wireless Networks (5 papers), COVID-19 diagnosis using AI (3 papers), AI in cancer detection (3 papers), Mobile Ad Hoc Networks (3 papers) and Indoor and Outdoor Localization Technologies (2 papers). The work is most often cited by research in Health Information Management (74 citations), Health Informatics (23 citations), Computer Networks and Communications (296 citations), Computer Vision and Pattern Recognition (123 citations) and Neurology (36 citations). Vipul Narayan has collaborated with scholars based in India, South Africa and Poland. Frequent co-authors include A. K. Daniel, Pawan Kumar Mall, Swapnita Srivastava, Mohammad Faiz, Maria Ganzha, Marcin Paprzycki, Pradeep Kumar Singh, Pooja Chaturvedi, Benjamin Teitelbaum and Susan Hares. Their work appears in journals such as Wireless Personal Communications, IET Wireless Sensor Systems, IEEE Network, Cluster Computing and Journal of Food Quality.

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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