Devi Thiyagarajan

712 citations
67 papers · 383 · h-index 11

Impact in

Papers in

    • Blockchain Technology Applications and Security 10
    • Cloud Data Security Solutions 7
    • Spam and Phishing Detection 5
    • Cloud Computing and Resource Management 4
    • Text and Document Classification Technologies 4

Devi Thiyagarajan

54 papers receiving 359 citations

Peers

Devi Thiyagarajan
Comparison fields: 5 of 76
  • Health Information Management 21
  • Information Systems 95
  • Analytical Chemistry 35
  • Computer Vision and Pattern Recognition 58
  • Computer Networks and Communications 62
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G. Geetha India
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Citations per field
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Citations per year

Countries citing papers authored by Devi Thiyagarajan

Since Specialization
Citations

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

Fields of papers citing papers by Devi Thiyagarajan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Devi Thiyagarajan, 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 Devi Thiyagarajan Line = papers co-authored together Devi Thiyagarajan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202291
2 202222
3 201518
4 202118
5 202217
6 202117
7 202117
8 202114
9 202212
10 202312
11 201911
12 202210
13
Automatic Emotion Recognition Using Facial Expression by Python
20199
14 20219
15 20228
16 20237
17 20236
18 20226
19 20145
20 20235

About Devi Thiyagarajan

Devi Thiyagarajan is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 67 papers that have together received 383 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (10 papers), Cloud Data Security Solutions (7 papers), COVID-19 diagnosis using AI (5 papers), Spam and Phishing Detection (5 papers), Cloud Computing and Resource Management (4 papers), Text and Document Classification Technologies (4 papers), IoT and Edge/Fog Computing (4 papers) and Advanced Malware Detection Techniques (4 papers). The work is most often cited by research in Health Information Management (21 citations), Information Systems (95 citations), Analytical Chemistry (35 citations), Computer Vision and Pattern Recognition (58 citations) and Computer Networks and Communications (62 citations). Devi Thiyagarajan has collaborated with scholars based in India, Iraq and Ethiopia. Frequent co-authors include N. Deepa, R. Ganesan, N. Deepa, M. Sambath, Abhishek Raghuvanshi, Bhupesh Kumar Singh, N. Lakshmi Gayathri, Anirudh Ramachandran, R. Seetharaman and R. Santhana Krishnan. Their work appears in journals such as International Journal of Technology, European Journal of Organic Chemistry, Materials Today Proceedings, Journal of Food Quality and Communications in computer and information science.

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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