M. E. Paramasivam

588 total citations
27 papers, 362 citations indexed

About

M. E. Paramasivam is a scholar working on Computer Vision and Pattern Recognition, Civil and Structural Engineering and Media Technology. According to data from OpenAlex, M. E. Paramasivam has authored 27 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Civil and Structural Engineering and 4 papers in Media Technology. Recurrent topics in M. E. Paramasivam's work include Industrial Vision Systems and Defect Detection (4 papers), Corrosion Behavior and Inhibition (3 papers) and Smart Agriculture and AI (3 papers). M. E. Paramasivam is often cited by papers focused on Industrial Vision Systems and Defect Detection (4 papers), Corrosion Behavior and Inhibition (3 papers) and Smart Agriculture and AI (3 papers). M. E. Paramasivam collaborates with scholars based in India, United States and United Kingdom. M. E. Paramasivam's co-authors include R. S. Sabeenian, S. Venkatakrishna Iyer, Y. Wang, Juha Kere, Ankur Thomas, Glenn D. Rosen, Joseph J. LoTurco, Jilin Bai, Nina Kaminen‐Ahola and Jan L. A. Voskuil and has published in prestigious journals such as Neuroscience, IEEE Transactions on Multimedia and Journal of Applied Electrochemistry.

In The Last Decade

M. E. Paramasivam

24 papers receiving 311 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. E. Paramasivam India	10	72	66	65	56	51	27	362
Won-Hyung Lee South Korea	10	88 1.2×	56 0.8×	6 0.1×	23 0.4×	7 0.1×	57	407
Ronghua Zhang China	10	10 0.1×	47 0.7×	6 0.1×	53 0.9×	8 0.2×	45	545
Zhiguo Wang China	18	76 1.1×	63 1.0×	4 0.1×	77 1.4×	29 0.6×	89	917
Johannes Zagermann Germany	14	39 0.5×	9 0.1×	6 0.1×	31 0.6×	9 0.2×	38	795
Wojciech Jaśkowski Poland	14	37 0.5×	17 0.3×	53 0.8×	144 2.6×	2 0.0×	41	690
Bobby D. Bryant United States	10	48 0.7×	40 0.6×	13 0.2×	17 0.3×	2 0.0×	23	549
Zhongzhou Chen United States	13	110 1.5×	71 1.1×	10 0.2×	40 0.7×	22 0.4×	51	770
Lanfang Sun China	12	14 0.2×	20 0.3×	4 0.1×	175 3.1×	18 0.4×	24	479

Countries citing papers authored by M. E. Paramasivam

Since Specialization

Citations

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

Fields of papers citing papers by M. E. Paramasivam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. E. Paramasivam. 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 M. E. Paramasivam. The network helps show where M. E. Paramasivam may publish in the future.

Co-authorship network of co-authors of M. E. Paramasivam

This figure shows the co-authorship network connecting the top 25 collaborators of M. E. Paramasivam. A scholar is included among the top collaborators of M. E. Paramasivam 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 M. E. Paramasivam. M. E. Paramasivam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Paramasivam, M. E.. (2025). Analysis of leakage mechanisms in Fully Depleted Silicon-on-Insulator (FD SOI) devices. Microelectronics Journal. 163. 106769–106769.

Paramasivam, M. E., et al.. (2024). Smart Question Paper Generator Using Oracle Apex Framework. 1–5. 1 indexed citations

Paramasivam, M. E., et al.. (2024). Oral Cancer Detection Using Convolutional Neural Network. 1–6. 1 indexed citations

Paramasivam, M. E., et al.. (2024). Deep Learning-Based Prediction of Knee Innovative Practices. 1–6. 1 indexed citations

Paramasivam, M. E., et al.. (2024). Revolutionizing Road Safety: AI-Powered Road Defect Detection. 147–152. 1 indexed citations

Akilandeswari, J., et al.. (2022). Design and development of an indoor navigation system using denoising autoencoder based convolutional neural network for visually impaired people. Multimedia Tools and Applications. 81(3). 3483–3514. 19 indexed citations

Anandan, P., et al.. (2021). Data analytics and resource planning using deep learning for overcoming challenges of COVID-19. Annals of the Romanian Society for Cell Biology. 25(2). 1884–1889. 4 indexed citations

Shanthi, T., M. E. Paramasivam, C. Prakash, et al.. (2021). Robust Fabric Defects Inspection System Using Deep Learning Architecture. Journal of Testing and Evaluation. 50(1). 646–655. 3 indexed citations

Sabeenian, R. S., et al.. (2017). Classification of Handwritten Tamil Characters in Palm Leaf Manuscripts Using SVM Based Smart Zoning Strategies. 18–21. 4 indexed citations

10.

Sabeenian, R. S., et al.. (2016). Appraisal of localized binarization methods on Tamil palm-leaf manuscripts. 793–797. 5 indexed citations

11.

Sabeenian, R. S., et al.. (2012). Computer Vision based Defect Detection and Identification in Handloom Silk Fabrics. International Journal of Computer Applications. 42(17). 41–48. 9 indexed citations

12.

Sabeenian, R. S., et al.. (2012). Identification and Counting of Fertile Pollen Grains using Morphological operators, FSF and CGF. International Journal of Computer Applications. 42(17). 36–40. 2 indexed citations

13.

Paramasivam, M. E. & R. S. Sabeenian. (2010). An efficient bit reduction binary multiplication algorithm using vedic methods. 25–28. 34 indexed citations

14.

Elango, A., et al.. (2009). Polyaniline as a corrosion inhibitor for commercial aluminium in alkaline solutions. 51(2). 97–104.

15.

Xodo, Luigi E., M. E. Paramasivam, Alexandro Membrino, & Susanna Cogoi. (2008). Protein hnRNPA1 binds to a critical G-rich element of KRAS and unwinds G-quadruplex structures: implications in transcription. Nucleic Acids Symposium Series. 52(1). 159–160. 17 indexed citations

16.

Pedersen, Erik B., Daniel Globisch, M. E. Paramasivam, et al.. (2008). Triplex glue by synthesizing conjugated flexible intercalators. Nucleic Acids Symposium Series. 52(1). 37–38. 2 indexed citations

17.

Wang, Y., M. E. Paramasivam, Ankur Thomas, et al.. (2006). DYX1C1 functions in neuronal migration in developing neocortex. Neuroscience. 143(2). 515–522. 115 indexed citations

18.

Kolandaivelu, Saravanan, M. E. Paramasivam, Sharmistha Dey, T.P. Singh, & Ashok Srinivasan. (2004). Biotinyl Endothelin-1 Binding to Endothelin Receptor and its Applications. Journal of Cardiovascular Pharmacology. 44(3). 287–293. 3 indexed citations

19.

Jayachandran, M., M. E. Paramasivam, K. R. Murali, D.C. Trivedi, & M. Raghavan. (2001). SYNTHESIS OF POROUS SILICON NANOSTRUCTURES FOR PHOTOLUMINESCENT DEVICES. Institutional Repository @ Central Electrochemical Research Institute (Central Electrochemical Research Institute). 6(2). 143–147. 13 indexed citations

20.

Paramasivam, M. E. & S. Venkatakrishna Iyer. (2001). Influence of alloying additives on corrosion and hydrogen permeation through commercial aluminium in alkaline solution. Journal of Applied Electrochemistry. 31(1). 115–119. 21 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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