T. Shanthi
Impact in
-
- Artificial Intelligence in Healthcare
- Ophthalmology top 5%
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
Papers in
-
- Computer Science and Engineering 2
-
- COVID-19 diagnosis using AI 2
- Retinal Imaging and Analysis 2
- Co-authors
- R. S. Sabeenian (6 shared papers)R. Anand (7 shared papers)S. Veni (4 shared papers)D. Raja (1 shared paper)K. Hareesh (1 shared paper)R. S. Anand (1 shared paper)V. Vijayabaskar (1 shared paper)C. Prakash (1 shared paper)
- Journals
- Computers & Electrical Engineering (1 paper)Journal of Testing and Evaluation (1 paper)Microprocessors and Microsystems (1 paper)International Journal of Intelligent Enterprise (2 papers)SHILAP Revista de lepidopterología (1 paper)
In The Last Decade
T. Shanthi
8 papers receiving 365 citations
T. Shanthi's Hit Papers
Peers
Comparison fields: 5 of 85
- Health Information Management 69
- Ophthalmology 89
- Radiology, Nuclear Medicine and Imaging 202
- Computer Vision and Pattern Recognition 142
- Artificial Intelligence 108
Countries citing papers authored by T. Shanthi
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
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-authors
The 9 scholars most cited alongside T. Shanthi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Modified Alexnet architecture for classification of diabetic retinopathy images Hit paper breakdown → | 2019 | 246 |
| 2 | 2020 | 102 | |
| 3 | Review of Feature Extraction Techniques in Automatic Speech Recognition | 2013 | 27 |
| 4 | 2020 | 19 | |
| 5 | 2020 | 10 | |
| 6 | 2020 | 10 | |
| 7 | 2021 | 6 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 1 | |
| 10 | 2021 | 1 |
About T. Shanthi
T. Shanthi is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 10 papers that have together received 425 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (2 papers), Smart Systems and Machine Learning (2 papers), Handwritten Text Recognition Techniques (2 papers), Retinal Imaging and Analysis (2 papers), Computer Science and Engineering (2 papers), Vehicle License Plate Recognition (2 papers), Music and Audio Processing (2 papers) and Animal Vocal Communication and Behavior (1 paper). The work is most often cited by research in Health Information Management (69 citations), Ophthalmology (89 citations), Radiology, Nuclear Medicine and Imaging (202 citations), Computer Vision and Pattern Recognition (142 citations) and Artificial Intelligence (108 citations). T. Shanthi has collaborated with scholars based in India, Thailand and Singapore. Frequent co-authors include R. S. Sabeenian, R. Anand, S. Veni, D. Raja, K. Hareesh, R. S. Anand, V. Vijayabaskar, C. Prakash and M. E. Paramasivam. Their work appears in journals such as Computers & Electrical Engineering, Journal of Testing and Evaluation, Microprocessors and Microsystems, International Journal of Intelligent Enterprise and SHILAP Revista de lepidopterología.
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.