S. Kannimuthu

631 total citations
46 papers, 387 citations indexed

About

S. Kannimuthu is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, S. Kannimuthu has authored 46 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Information Systems, 20 papers in Artificial Intelligence and 11 papers in Computer Networks and Communications. Recurrent topics in S. Kannimuthu's work include Data Mining Algorithms and Applications (12 papers), Rough Sets and Fuzzy Logic (8 papers) and Imbalanced Data Classification Techniques (5 papers). S. Kannimuthu is often cited by papers focused on Data Mining Algorithms and Applications (12 papers), Rough Sets and Fuzzy Logic (8 papers) and Imbalanced Data Classification Techniques (5 papers). S. Kannimuthu collaborates with scholars based in India, United States and Iraq. S. Kannimuthu's co-authors include K. Premalatha, D.K. Subramanian, K. S. Bhuvaneshwari, Shashi Kant Shankar, M. Anand Kumar, M. Prakash, S. T. Suganthi, Shankar Subramanian, Nebojša Bačanin and S. Nandhini and has published in prestigious journals such as IEEE Access, Biomedical Signal Processing and Control and Mobile Networks and Applications.

In The Last Decade

S. Kannimuthu

40 papers receiving 353 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Kannimuthu India 12 189 156 83 48 46 46 387
Matin Pirouz United States 13 200 1.1× 183 1.2× 81 1.0× 58 1.2× 67 1.5× 34 482
Baljeet Kaur India 11 204 1.1× 27 0.2× 61 0.7× 33 0.7× 49 1.1× 53 490
Anirban Mitra India 12 94 0.5× 62 0.4× 46 0.6× 39 0.8× 19 0.4× 49 405
Mohammad Shafiul Alam Bangladesh 12 197 1.0× 31 0.2× 42 0.5× 18 0.4× 20 0.4× 44 421
Mihaela Dînșoreanu Romania 11 145 0.8× 158 1.0× 11 0.1× 116 2.4× 27 0.6× 68 344
Amadeo-José Argüelles-Cruz Mexico 11 122 0.6× 44 0.3× 15 0.2× 39 0.8× 17 0.4× 52 315
Diwakar Tripathi India 16 375 2.0× 53 0.3× 34 0.4× 29 0.6× 19 0.4× 31 582
P.S. Yu United States 10 256 1.4× 176 1.1× 20 0.2× 115 2.4× 47 1.0× 14 436
Haoran Tang China 6 270 1.4× 37 0.2× 47 0.6× 28 0.6× 16 0.3× 21 380

Countries citing papers authored by S. Kannimuthu

Since Specialization
Citations

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

Fields of papers citing papers by S. Kannimuthu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Kannimuthu

This figure shows the co-authorship network connecting the top 25 collaborators of S. Kannimuthu. A scholar is included among the top collaborators of S. Kannimuthu 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 S. Kannimuthu. S. Kannimuthu 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.
Kannimuthu, S., et al.. (2024). Cosine deep convolutional neural network for Parkinson’s disease detection and severity level classification using hand drawing spiral image in IoT platform. Biomedical Signal Processing and Control. 94. 106220–106220. 12 indexed citations
2.
Kannimuthu, S., et al.. (2024). Practice challenge recommendations in online judge using implicit rating extraction and utility sequence patterns. Data Technologies and Applications. 58(5). 718–741. 1 indexed citations
3.
4.
Kannimuthu, S., et al.. (2023). An Adaptive Intelligent Polar Bear (AIPB) Optimization-Quantized Contempo Neural Network (QCNN) model for Parkinson’s disease diagnosis using speech dataset. Biomedical Signal Processing and Control. 87. 105467–105467. 6 indexed citations
5.
Nandhini, S. & S. Kannimuthu. (2023). Mining high average utility itemsets using artificial fish swarm algorithm with computed multiple minimum average utility thresholds. Journal of Intelligent & Fuzzy Systems. 46(1). 1597–1613. 3 indexed citations
6.
Kannimuthu, S., et al.. (2023). Deep learning-based feature selection and prediction system for autism spectrum disorder using a hybrid meta-heuristics approach. Journal of Intelligent & Fuzzy Systems. 45(1). 797–807. 8 indexed citations
7.
Prakash, M., et al.. (2022). An Enhanced Localization Approach for Energy Conservation in Wireless Sensor Network with Q Deep Learning Algorithm. Symmetry. 14(12). 2515–2515. 8 indexed citations
8.
Kannimuthu, S., et al.. (2022). Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns. Intelligent Automation & Soft Computing. 35(3). 3845–3860. 4 indexed citations
9.
Kannimuthu, S., et al.. (2022). Discovery of Interesting Itemsets for Web Service Composition Using Hybrid Genetic Algorithm. Neural Processing Letters. 54(5). 3913–3939. 8 indexed citations
10.
Kannimuthu, S., et al.. (2022). Author Profiling in Code-Mixed WhatsApp Messages Using Stacked Convolution Networks and Contextualized Embedding Based Text Augmentation. Neural Processing Letters. 55(1). 589–614. 17 indexed citations
11.
Kannimuthu, S. & A. Arunkumar. (2021). Machine Learning Based Approach For Corona Virus Disease Recovery Prediction. 12(3). 1188–1199. 2 indexed citations
12.
Kannimuthu, S., et al.. (2020). An Integration of Big Data Analytics and Cyber Security-A Panoramic Survey. SSRN Electronic Journal.
13.
Kannimuthu, S., et al.. (2019). KCE DALab-APDA@FIRE2019: Author Profiling and Deception Detection in Arabic using Weighted Embedding.. 136–143. 1 indexed citations
14.
Kannimuthu, S., et al.. (2019). Performance Evaluation of Machine Learning Algorithms for Dengue Disease Prediction. Journal of Computational and Theoretical Nanoscience. 16(12). 5105–5110. 13 indexed citations
15.
Kannimuthu, S., et al.. (2018). KCE_DAlab@MAPonSMS-FIRE2018: Effective word and character-based features for Multilingual Author Profiling.. 213–222. 1 indexed citations
16.
Kannimuthu, S., et al.. (2018). Deep Learning Techniques for Polarity Classification in Multimodal Sentiment Analysis. International Journal of Information Technology & Decision Making. 17(3). 883–910. 28 indexed citations
17.
Bhuvaneshwari, K. S., et al.. (2018). Probabilistic variable precision fuzzy rough set technique for discovering optimal learning patterns in e-learning. International Journal of Business Intelligence and Data Mining. 14(1/2). 121–121.
18.
Kannimuthu, S., et al.. (2017). KEC_DAlab @ EventXtract-IL-FIRE2017: Event Extraction using Support Vector Machines.. 144–146. 1 indexed citations
19.
Kannimuthu, S., et al.. (2017). A secure cross-layer AODV routing method to detect and isolate (SCLARDI) black hole attacks for MANET. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 25. 2761–2769. 9 indexed citations
20.
Kannimuthu, S., K. Premalatha, & Shankar Subramanian. (2013). A Novel Approach to Extract High Utility Itemsets from Distributed Databases. Computing and Informatics / Computers and Artificial Intelligence. 31. 1597–1615. 9 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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2026