T. Kalaiselvi

798 total citations
49 papers, 518 citations indexed

About

T. Kalaiselvi is a scholar working on Computer Vision and Pattern Recognition, Neurology and Artificial Intelligence. According to data from OpenAlex, T. Kalaiselvi has authored 49 papers receiving a total of 518 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Computer Vision and Pattern Recognition, 32 papers in Neurology and 9 papers in Artificial Intelligence. Recurrent topics in T. Kalaiselvi's work include Brain Tumor Detection and Classification (32 papers), Medical Image Segmentation Techniques (31 papers) and Advanced Neural Network Applications (9 papers). T. Kalaiselvi is often cited by papers focused on Brain Tumor Detection and Classification (32 papers), Medical Image Segmentation Techniques (31 papers) and Advanced Neural Network Applications (9 papers). T. Kalaiselvi collaborates with scholars based in India and United States. T. Kalaiselvi's co-authors include K. Somasundaram, P. Sriramakrishnan, S. Padmapriya, Rajeswaran Rangasami, P. Balasubramaniam, N. Shanthi, S. Vijayalakshmi, Seepana Praveenkumar, S. Ramkumar and R. Krishnamoorthy and has published in prestigious journals such as Neural Computing and Applications, Computers in Biology and Medicine and Biomedical Signal Processing and Control.

In The Last Decade

T. Kalaiselvi

47 papers receiving 479 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. Kalaiselvi India 12 366 316 112 108 43 49 518
Jainy Sachdeva India 11 409 1.1× 390 1.2× 126 1.1× 162 1.5× 87 2.0× 19 595
Waheed Ahmed Abro China 13 246 0.7× 217 0.7× 52 0.5× 257 2.4× 24 0.6× 19 500
P. Sriramakrishnan India 10 184 0.5× 188 0.6× 74 0.7× 93 0.9× 13 0.3× 28 314
Nilesh Bhaskarrao Bahadure India 7 398 1.1× 477 1.5× 105 0.9× 173 1.6× 39 0.9× 31 648
Asim Munir Pakistan 10 245 0.7× 167 0.5× 134 1.2× 186 1.7× 43 1.0× 21 486
Zaka Ur Rehman Malaysia 8 265 0.7× 179 0.6× 197 1.8× 117 1.1× 19 0.4× 22 488
P. Kalavathi India 10 246 0.7× 152 0.5× 101 0.9× 56 0.5× 28 0.7× 30 383
Abdel-Badeeh M. Salem Egypt 10 346 0.9× 430 1.4× 92 0.8× 211 2.0× 19 0.4× 23 648
S. Ramathilagam India 11 219 0.6× 65 0.2× 38 0.3× 166 1.5× 72 1.7× 21 384
Mohd Abdul Hameed India 8 220 0.6× 245 0.8× 97 0.9× 184 1.7× 11 0.3× 27 456

Countries citing papers authored by T. Kalaiselvi

Since Specialization
Citations

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

Fields of papers citing papers by T. Kalaiselvi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

This figure shows the co-authorship network connecting the top 25 collaborators of T. Kalaiselvi. A scholar is included among the top collaborators of T. Kalaiselvi 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. Kalaiselvi. T. Kalaiselvi 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.
Kalaiselvi, T., et al.. (2025). An Automatic Mango Quality Grading System in Smart Agriculture using Novel Adaptive Feature Vector and Ensemble Learning. Multimedia Tools and Applications. 84(31). 38045–38070.
2.
Padmapriya, S., et al.. (2024). Improving the Prediction Accuracy of MRI Brain TumorDetection and Segmentation. International Journal of Computing and Digital Systems. 15(1). 499–509. 4 indexed citations
3.
Sriramakrishnan, P., et al.. (2024). RIBM3DU‐Net: Glioma tumour substructures segmentation in magnetic resonance images using residual‐inception block with modified 3D U‐Net architecture. International Journal of Imaging Systems and Technology. 34(2). 6 indexed citations
4.
Kalaiselvi, T., et al.. (2024). ASP-DSRN: Accurate Seizure Prediction Using Dual Self-Attention Residual Networking Model. 140. 1–7. 1 indexed citations
5.
Kalaiselvi, T., et al.. (2021). Enhanced Non Local Means Filter to Denoise MR Brain Images by Using Mean Absolute Deviation Error Measure. Journal of Cardiovascular Disease Research. 12(2). 63–69.
6.
7.
Kalaiselvi, T., et al.. (2020). Development of automatic glioma brain tumor detection system using deep convolutional neural networks. International Journal of Imaging Systems and Technology. 30(4). 926–938. 20 indexed citations
8.
Sriramakrishnan, P., et al.. (2019). Online Brain Image Repositories for Brain Disease Detection. International Journal of Innovative Technology and Exploring Engineering. 9(2S2). 864–867. 1 indexed citations
9.
Sriramakrishnan, P., et al.. (2019). A Role of Medical Imaging Techniques in Human Brain Tumor Treatment. International Journal of Recent Technology and Engineering (IJRTE). 8(4S2). 565–568. 1 indexed citations
10.
Kalaiselvi, T., et al.. (2019). Three-Phase Automatic Brain Tumor Diagnosis System Using Patches Based Updated Run Length Region Growing Technique. Journal of Digital Imaging. 33(2). 465–479. 21 indexed citations
11.
Kalaiselvi, T., et al.. (2019). Reliability of Segmenting Brain Tumor and Finding Optimal Volume Estimator for MR Images of Patients with Glioma’s. International Journal of Innovative Technology and Exploring Engineering. 8(9). 1647–1653. 2 indexed citations
12.
Sriramakrishnan, P., et al.. (2019). An Medical Image File Formats and Digital Image Conversion. International Journal of Engineering and Advanced Technology. 9(1s4). 74–78. 11 indexed citations
13.
Kalaiselvi, T. & P. Sriramakrishnan. (2018). Rapid brain tissue segmentation process by modified FCM algorithm with CUDA enabled GPU machine. International Journal of Imaging Systems and Technology. 28(3). 163–174. 9 indexed citations
14.
Kalaiselvi, T., et al.. (2018). Multi-Item Production Inventory Model With Remanufacturing of Defective Items and Return Items Using Hexagonal Fuzzy Number. Journal of Emerging Technologies and Innovative Research. 5(2). 738-745–738-745. 1 indexed citations
15.
Kalaiselvi, T., P. Sriramakrishnan, & K. Somasundaram. (2018). Performance of Medical Image Processing Algorithms Implemented in CUDA running on GPU based Machine. International Journal of Intelligent Systems and Applications. 10(1). 58–68. 4 indexed citations
16.
Kalaiselvi, T., et al.. (2016). An Automatic Segmentation of Brain Tumor from MRI Scans through Wavelet Transformations. International Journal of Image Graphics and Signal Processing. 8(11). 59–65. 8 indexed citations
17.
Kalaiselvi, T., P. Sriramakrishnan, & K. Somasundaram. (2016). Brain abnormality detection from MRI of human head scans using the bilateral symmetry property and histogram similarity measures. 1–6. 3 indexed citations
18.
Somasundaram, K. & T. Kalaiselvi. (2009). A Comparative Study of Segmentation Techniques used for MR Brain Images.. IPCV. 597–603. 10 indexed citations
19.
Somasundaram, K. & T. Kalaiselvi. (2009). A Novel Technique for Finding the Boundary between the Cerebral Hemispheres from MR Axial Head Scans.. 1486–1502. 7 indexed citations
20.
Kalaiselvi, T. & Kalavathy Ramasamy. (1996). COMPOST MATURITY: CAN IT BE EVALUATED?. Madras Agricultural Journal. 83(October). 609–618. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Jainy Sachdeva Breakdown of academic impact, for papers by Waheed Ahmed Abro Breakdown of academic impact, for papers by P. Sriramakrishnan Breakdown of academic impact, for papers by Nilesh Bhaskarrao Bahadure Breakdown of academic impact, for papers by Asim Munir Breakdown of academic impact, for papers by Zaka Ur Rehman Breakdown of academic impact, for papers by P. Kalavathi Breakdown of academic impact, for papers by Abdel-Badeeh M. Salem Breakdown of academic impact, for papers by S. Ramathilagam Breakdown of academic impact, for papers by Mohd Abdul Hameed
Rankless by CCL
2026