R. Subhashini

616 citations
71 papers · 311 · h-index 8

Impact in

Papers in

R. Subhashini

51 papers receiving 267 citations

Peers

R. Subhashini
Comparison fields: 5 of 92
  • Health Information Management 15
  • Artificial Intelligence 92
  • Signal Processing 28
  • Computer Vision and Pattern Recognition 52
  • Information Systems 55
Replace Etinosa Noma‐Osaghae with:
Etinosa Noma‐Osaghae Nigeria
Maman Abdurohman Indonesia
Ninni Singh India
Amanpreet Singh India
Jyoti Agarwal India
Punit Rathore Australia
Loc Nguyen United States
Anurag Sharma Fiji
R. Krishnamoorthy India
R. Subhashini relative to Etinosa Noma‐Osaghae Nigeria Etinosa Noma‐Osaghae's profile →
Citations per field
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Etinosa Noma‐Osaghae · 1×
Citations per year

Countries citing papers authored by R. Subhashini

Since Specialization
Citations

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

Fields of papers citing papers by R. Subhashini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside R. Subhashini, 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 R. Subhashini Line = papers co-authored together R. Subhashini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201685
2 201034
3 201517
4 201412
5 201011
6 201410
7 201710
8 20197
9 20217
10 20157
11 20236
12 20166
13 20186
14 20236
15 20196
16 20215
17 20195
18 20205
19 20174
20 20194

About R. Subhashini

R. Subhashini is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 71 papers that have together received 311 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Spam and Phishing Detection (5 papers), Advanced Malware Detection Techniques (4 papers), Sentiment Analysis and Opinion Mining (4 papers), Data Management and Algorithms (3 papers), Natural Language Processing Techniques (3 papers), IoT-based Smart Home Systems (3 papers) and Water Quality Monitoring Technologies (3 papers). The work is most often cited by research in Health Information Management (15 citations), Artificial Intelligence (92 citations), Signal Processing (28 citations), Computer Vision and Pattern Recognition (52 citations) and Information Systems (55 citations). R. Subhashini has collaborated with scholars based in India, Malaysia and Philippines. Frequent co-authors include John V. Thomas, P. Jeyanthi, V. Maria Anu, R. Anitha, Raj Sethuraman, S. Saravanan, R Surendran, Mary Subaja Christo, S. Bharathi and N. Venkateswaran. Their work appears in journals such as Indian Journal of Science and Technology, Future Internet, Knowledge-Based Systems, Neural Processing Letters and National Academy Science Letters.

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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