T. Shanthi

725 total citations · 1 hit paper
10 papers, 425 citations indexed

About

T. Shanthi is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, T. Shanthi has authored 10 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in T. Shanthi's work include Retinal Imaging and Analysis (2 papers), Handwritten Text Recognition Techniques (2 papers) and Music and Audio Processing (2 papers). T. Shanthi is often cited by papers focused on Retinal Imaging and Analysis (2 papers), Handwritten Text Recognition Techniques (2 papers) and Music and Audio Processing (2 papers). T. Shanthi collaborates with scholars based in India, Singapore and Thailand. T. Shanthi's co-authors include R. S. Sabeenian, R. Anand, S. Veni, C. Prakash, D. Raja, M. E. Paramasivam, R. S. Anand, K. Hareesh and V. Vijayabaskar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers & Electrical Engineering and Journal of Testing and Evaluation.

In The Last Decade

T. Shanthi

8 papers receiving 365 citations

Hit Papers

Modified Alexnet architecture for classification of diabe... 2019 2026 2021 2023 2019 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Shanthi India 7 202 142 108 89 69 10 425
Peyman Hosseinzadeh Kassani United States 10 219 1.1× 171 1.2× 222 2.1× 83 0.9× 64 0.9× 13 513
Walaa Gouda Saudi Arabia 10 163 0.8× 104 0.7× 267 2.5× 41 0.5× 29 0.4× 16 501
Mostafa E. A. Ibrahim Egypt 10 79 0.4× 118 0.8× 62 0.6× 55 0.6× 20 0.3× 29 343
P. C. Siddalingaswamy India 12 216 1.1× 165 1.2× 223 2.1× 114 1.3× 10 0.1× 34 538
Isam Abu‐Qasmieh Jordan 13 178 0.9× 77 0.5× 226 2.1× 27 0.3× 8 0.1× 39 604
Muyi Sun China 13 188 0.9× 229 1.6× 107 1.0× 76 0.9× 11 0.2× 38 556
Suman Sedai Australia 10 178 0.9× 201 1.4× 79 0.7× 105 1.2× 10 0.1× 25 359
J. Dheeba India 9 230 1.1× 185 1.3× 315 2.9× 45 0.5× 57 0.8× 25 496
Pedro Costa Portugal 12 360 1.8× 265 1.9× 166 1.5× 157 1.8× 52 0.8× 21 596
Lituan Wang China 10 197 1.0× 209 1.5× 247 2.3× 37 0.4× 8 0.1× 23 487

Countries citing papers authored by T. Shanthi

Since Specialization
Citations

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

Fields of papers citing papers by T. Shanthi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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

All Works

10 of 10 papers shown
1.
Shanthi, T., et al.. (2021). FUNDUS IMAGE CLASSIFICATION USING HYBRIDIZED GLCM FEATURES AND WAVELET FEATURES. SHILAP Revista de lepidopterología. 11(3). 2372–2374. 1 indexed citations
2.
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
3.
Shanthi, T., et al.. (2021). Automatic Social Distance Monitoring system using Deep Learning Algorithms. IOP Conference Series Earth and Environmental Science. 785(1). 12016–12016. 1 indexed citations
4.
Anand, R., et al.. (2021). AI based Birds Sound Classification Using Convolutional Neural Networks. IOP Conference Series Earth and Environmental Science. 785(1). 12015–12015. 6 indexed citations
5.
Anand, R., et al.. (2020). Detection and identification of COVID -19 based on chest medical image by using convolutional neural networks. PubMed Central. 1. 112–118. 10 indexed citations
6.
Shanthi, T., R. S. Sabeenian, & R. Anand. (2020). Automatic diagnosis of skin diseases using convolution neural network. Microprocessors and Microsystems. 76. 103074–103074. 102 indexed citations
7.
Anand, R., T. Shanthi, R. S. Sabeenian, & S. Veni. (2020). Real time noisy dataset implementation of optical character identification using CNN. International Journal of Intelligent Enterprise. 7(1/2/3). 67–67. 19 indexed citations
8.
Veni, S., R. S. Sabeenian, T. Shanthi, & R. Anand. (2020). Real time noisy dataset implementation of optical character identification using CNN. International Journal of Intelligent Enterprise. 7(1/3). 67–67. 10 indexed citations
9.
Shanthi, T. & R. S. Sabeenian. (2019). Modified Alexnet architecture for classification of diabetic retinopathy images. Computers & Electrical Engineering. 76. 56–64. 246 indexed citations breakdown →
10.
Shanthi, T., et al.. (2013). Review of Feature Extraction Techniques in Automatic Speech Recognition. International Journal of Scientific Engineering and Technology. 2(6). 479–484. 27 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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