C. Nalini

692 total citations
39 papers, 292 citations indexed

About

C. Nalini is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, C. Nalini has authored 39 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 8 papers in Information Systems. Recurrent topics in C. Nalini's work include COVID-19 diagnosis using AI (4 papers), Software Reliability and Analysis Research (4 papers) and Software Engineering Research (3 papers). C. Nalini is often cited by papers focused on COVID-19 diagnosis using AI (4 papers), Software Reliability and Analysis Research (4 papers) and Software Engineering Research (3 papers). C. Nalini collaborates with scholars based in India, United States and Iraq. C. Nalini's co-authors include A. Sangeetha, N. Kumar, A. Kumaravel, Shashank Joshi, Devendra Kumar, M. Amina Begum, Allam Balaram, Praveen Kumar, P. Anandan and V. R. Niveditha and has published in prestigious journals such as Sustainable Energy Technologies and Assessments, International Journal of Nanotechnology and EAI Endorsed Transactions on Pervasive Health and Technology.

In The Last Decade

C. Nalini

32 papers receiving 282 citations

Peers

C. Nalini
Ying Sheng United States
Nam-Su Jho South Korea
Dian Shen China
Ying Sheng United States
C. Nalini
Citations per year, relative to C. Nalini C. Nalini (= 1×) peers Ying Sheng

Countries citing papers authored by C. Nalini

Since Specialization
Citations

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

Fields of papers citing papers by C. Nalini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. Nalini

This figure shows the co-authorship network connecting the top 25 collaborators of C. Nalini. A scholar is included among the top collaborators of C. Nalini 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 C. Nalini. C. Nalini 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
4.
Nalini, C., et al.. (2024). Predicting and Propagation of Diabetic Foot Infection by Deep Learning Model. EAI Endorsed Transactions on Pervasive Health and Technology. 10. 3 indexed citations
7.
Nalini, C., et al.. (2023). COVID-19 detection and tracking using smart applications with artificial intelligence. International Journal of Nanotechnology. 20(1/2/3/4). 433–449. 1 indexed citations
8.
Anandan, P., et al.. (2023). A mutual certificate-based data privacy scheme for ubiquitous and sustainable computing system users. Sustainable Energy Technologies and Assessments. 58. 103356–103356. 1 indexed citations
9.
Nalini, C., et al.. (2019). An Efficient Component based Analysis of Optical Character Recognition. International Journal of Innovative Technology and Exploring Engineering. 8(12S). 1117–1120. 1 indexed citations
10.
Nalini, C., et al.. (2019). Relationship Identification & Prediction of Diseases Association using Micro-RNA of Genomic Data. International Journal of Innovative Technology and Exploring Engineering. 8(9S3). 1093–1096. 1 indexed citations
11.
Nalini, C., et al.. (2019). Preprocessing Medical Images for Classification using Deep Learning Techniques. International Journal of Innovative Technology and Exploring Engineering. 8(9S3). 711–716. 4 indexed citations
12.
Nalini, C., et al.. (2019). 3D MR Image Denoising using higher Order Kernel Regression. International Journal of Innovative Technology and Exploring Engineering. 8(9S3). 1077–1086. 1 indexed citations
13.
Nalini, C., et al.. (2019). Efficient Notes Generation through Information Extraction. International Journal of Engineering and Advanced Technology. 8(6s2). 160–162.
14.
Nalini, C., et al.. (2019). A Systematic Judgment to Automated Programming Contracts Generation. International Journal of Recent Technology and Engineering (IJRTE). 8(2). 5017–5025. 2 indexed citations
15.
Nalini, C., et al.. (2019). Improving DDoS Attack Predection Performance using Ensambling Techniqes. International Journal of Recent Technology and Engineering (IJRTE). 8(3). 4760–4763. 1 indexed citations
16.
Nalini, C., et al.. (2019). Application for 3D Interface using Augmented Reality. International Journal of Engineering and Advanced Technology. 8(6s2). 694–695. 1 indexed citations
17.
Nalini, C., et al.. (2015). Learning Image Re-Rank: Query-DependentImage Re-Ranking Using Semantic Signature. International Journal of Innovative Research in Science Engineering and Technology. 4(3). 1489–1496. 2 indexed citations
18.
Nalini, C., et al.. (2015). Observing the Effects of Colored Lenses onIris Recognition using Feature ExtractionTechnique. International Journal of Innovative Research in Science Engineering and Technology. 4(3). 1734–1740.
19.
Nalini, C., et al.. (2014). Churn Prediction using MAPREDUCE. International Journal of Scientific Engineering and Technology. 3(5). 597–600. 4 indexed citations
20.
Nalini, C., et al.. (2007). Optimized S-box design for AES core. 843–849. 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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