Vinayakumar Ravi

174 papers receiving 2.9k citations

Vinayakumar Ravi's Hit Papers

Deep Learning Approach for SDN-Enabled Intrusion Detection System in IoT Networks 2023 · 101 citations
1010+1+2Years since publication255075100

Peers

Vinayakumar Ravi
Comparison fields: 5 of 153
  • Signal Processing 737
  • Computer Networks and Communications 1.1k
  • Health Informatics 51
  • Artificial Intelligence 1.1k
  • Health Information Management 144
Replace Jafar A. Alzubi with:
Jafar A. Alzubi Jordan
Ahmed Ghoneim Saudi Arabia
Rutvij H. Jhaveri India
Shamsul Huda Australia
Mazhar Javed Awan Pakistan
Mohamed Hammad Egypt
Chan Yeob Yeun United Arab Emirates
A. Kannan India
Arash Heidari Iran
Chiranji Lal Chowdhary India
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Citations per field
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Jafar A. Alzubi · 1×
Citations per year

Countries citing papers authored by Vinayakumar Ravi

Since Specialization
Citations

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

Fields of papers citing papers by Vinayakumar Ravi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 202 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022129
2
Deep Learning Approach for SDN-Enabled Intrusion Detection System in IoT Networks
Hit paper breakdown →
2023101
3 2021100
4 202297
5 202294
6 202275
7 202274
8 202270
9 202266
10 202264
11 202163
12 202161
13 202159
14 202258
15 202357
16 202156
17 202151
18 202148
19 202244
20 202244

About Vinayakumar Ravi

Vinayakumar Ravi is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 202 papers that have together received 3.0k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (34 papers), Advanced Malware Detection Techniques (30 papers), COVID-19 diagnosis using AI (29 papers), AI in cancer detection (28 papers), Artificial Intelligence in Healthcare (16 papers), Radiomics and Machine Learning in Medical Imaging (16 papers), Brain Tumor Detection and Classification (15 papers) and Internet Traffic Analysis and Secure E-voting (14 papers). The work is most often cited by research in Signal Processing (737 citations), Computer Networks and Communications (1.1k citations), Health Informatics (51 citations), Artificial Intelligence (1.1k citations) and Health Information Management (144 citations). Vinayakumar Ravi has collaborated with scholars based in Saudi Arabia, India and United States. Frequent co-authors include Rajasekhar Chaganti, Tuan D. Pham, Mamoun Alazab, V. Sowmya, Vasundhara Acharya, Hemanta Kumar Bhuyan, Pooja Yadav, Chinmay Chakraborty, K. P. Soman and Soman K.P.. Their work appears in journals such as Multimedia Tools and Applications, IEEE Transactions on Engineering Management, Journal of Safety Science and Resilience, Transactions on Emerging Telecommunications Technologies and Scientific Reports.

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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