T. Velmurugan

874 total citations
49 papers, 616 citations indexed

About

T. Velmurugan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, T. Velmurugan has authored 49 papers receiving a total of 616 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 15 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in T. Velmurugan's work include Data Mining Algorithms and Applications (11 papers), Artificial Intelligence in Healthcare (9 papers) and AI in cancer detection (7 papers). T. Velmurugan is often cited by papers focused on Data Mining Algorithms and Applications (11 papers), Artificial Intelligence in Healthcare (9 papers) and AI in cancer detection (7 papers). T. Velmurugan collaborates with scholars based in India and United States. T. Velmurugan's co-authors include Anuradha Chug and T. Santhanam and has published in prestigious journals such as Applied Soft Computing, Mathematical Problems in Engineering and Indian Journal of Science and Technology.

In The Last Decade

T. Velmurugan

44 papers receiving 529 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
T. Velmurugan India 14 323 133 114 102 79 49 616
Abdulmohsen Algarni Saudi Arabia 14 309 1.0× 169 1.3× 142 1.2× 37 0.4× 41 0.5× 62 717
Veera Boonjing Thailand 12 246 0.8× 133 1.0× 54 0.5× 93 0.9× 13 0.2× 57 554
Hani Alshahrani Saudi Arabia 16 242 0.7× 151 1.1× 98 0.9× 72 0.7× 14 0.2× 65 746
Muhammad Shafiq China 15 124 0.4× 246 1.8× 90 0.8× 64 0.6× 21 0.3× 35 610
Nadim Obeid Jordan 14 400 1.2× 182 1.4× 87 0.8× 64 0.6× 12 0.2× 61 651
Lungan Zhang China 9 680 2.1× 234 1.8× 133 1.2× 33 0.3× 52 0.7× 10 892
Georgios Kostopoulos Greece 14 254 0.8× 72 0.5× 44 0.4× 58 0.6× 269 3.4× 23 573
Abhay Bansal India 14 220 0.7× 246 1.8× 85 0.7× 106 1.0× 168 2.1× 109 716
A. Kumaravel India 11 245 0.8× 176 1.3× 93 0.8× 44 0.4× 10 0.1× 51 824
S. Balamurugan India 12 263 0.8× 128 1.0× 77 0.7× 46 0.5× 15 0.2× 100 548

Countries citing papers authored by T. Velmurugan

Since Specialization
Citations

This map shows the geographic impact of T. Velmurugan'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 T. Velmurugan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Velmurugan more than expected).

Fields of papers citing papers by T. Velmurugan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Velmurugan

This figure shows the co-authorship network connecting the top 25 collaborators of T. Velmurugan. A scholar is included among the top collaborators of T. Velmurugan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with T. Velmurugan. T. Velmurugan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Velmurugan, T., et al.. (2023). Optimizing Facial Expression Recognition through Effective Preprocessing Techniques. Journal of Computer and Communications. 11(12). 86–101. 2 indexed citations
3.
Velmurugan, T., et al.. (2023). Emotion Deduction from Social Media Text Data Using Machine Learning Algorithm. Journal of Computer and Communications. 11(11). 183–196.
4.
Velmurugan, T., et al.. (2020). Impact of Customer Feedback System using Machine Learning Algorithms for Sentiment Mining. International Journal of Innovative Technology and Exploring Engineering. 9(4). 1475–1483. 1 indexed citations
5.
Velmurugan, T., et al.. (2020). Predicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term Memory. Journal of Computer Science. 16(10). 1428–1438. 2 indexed citations
6.
Velmurugan, T., et al.. (2019). Prediction of Heart Disease using Name Entity Recognition based on Back Propagation and Whale Optimization Algorithms. International Journal of Innovative Technology and Exploring Engineering. 8(10S). 437–443. 4 indexed citations
7.
Velmurugan, T., et al.. (2019). Heart Disease Prediction Using Optimal Name Recognition based on Deep Learning Models and Whale Optimization Algorithms. Journal of Advanced Research in Dynamic and Control Systems. 11. 808–816. 1 indexed citations
8.
Velmurugan, T., et al.. (2019). Preprocessing the Groundwater Quality data by LSR and QDR techniques. International Journal of Innovative Technology and Exploring Engineering. 9(2). 2636–2644. 2 indexed citations
9.
Velmurugan, T., et al.. (2019). Ascertaining Abnormal Regions in Mammogram Images using Gravitational Search Local Map View Technique. International Journal of Innovative Technology and Exploring Engineering. 8(9). 1861–1868. 2 indexed citations
10.
Velmurugan, T., et al.. (2019). Direct-Indirect Association Rule Mining for Online Shopping Customer Data using Natural Language Processing. International Journal of Recent Technology and Engineering (IJRTE). 8(4). 11099–11106. 2 indexed citations
11.
Velmurugan, T., et al.. (2017). Evaluation of lexicon- and syntax-based negation detection algorithms using clinical text data. Bio-Algorithms and Med-Systems. 13(4). 201–213. 2 indexed citations
12.
Velmurugan, T.. (2017). A State of Art Analysis of Telecommunication Data by k-Means and k-Medoids Clustering Algorithms. Journal of Computer and Communications. 6(1). 190–202. 4 indexed citations
13.
Velmurugan, T., et al.. (2016). A Survey on the Result Based Analysis of Student Performance using Data Mining Techniques. 5(1). 91–95. 1 indexed citations
14.
Chug, Anuradha & T. Velmurugan. (2016). Performance Evaluation of Feature Selection Algorithms in Educational Data Mining. 5(2). 131–139. 16 indexed citations
15.
Velmurugan, T., et al.. (2016). Classification Algorithm based analysis of Breast cancer data. 5(1). 43–49. 17 indexed citations
16.
Velmurugan, T., et al.. (2016). A Survey on Educational Data Mining Tools and Techniques. 5(2). 167–171.
17.
Velmurugan, T., et al.. (2016). Efficiency of k-Means and k-Medoids Clustering Algorithms using Lung Cancer Dataset. 5(2). 150–156. 8 indexed citations
18.
Velmurugan, T., et al.. (2015). Effective Approaches of Classification Algorithms for Text Mining Applications. 4(2). 103–107. 2 indexed citations
19.
Chug, Anuradha & T. Velmurugan. (2015). A Comparative Analysis on the Evaluation of Classification Algorithms in the Prediction of Students Performance. Indian Journal of Science and Technology. 8(15). 73 indexed citations
20.
Velmurugan, T., et al.. (2014). Clustering Lung Cancer Data by k-Means and k- Medoids Algorithms. 3(2). 95–98. 2 indexed citations

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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