G. Kavitha

418 citations
56 papers · 218 · h-index 8

Impact in

Papers in

G. Kavitha

46 papers receiving 203 citations

Peers

G. Kavitha
Comparison fields: 5 of 62
  • Health Information Management 24
  • Computer Vision and Pattern Recognition 105
  • Neurology 35
  • Radiology, Nuclear Medicine and Imaging 83
  • Media Technology 20
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Citations per field
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Citations per year

Countries citing papers authored by G. Kavitha

Since Specialization
Citations

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

Fields of papers citing papers by G. Kavitha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside G. Kavitha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with G. Kavitha Line = papers co-authored together G. Kavitha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202119
2 201417
3 202014
4 201513
5
Video Object Extraction Based on a Comparative Study of Efficient Edge Detection Techniques
200911
6 201910
7 20098
8 20238
9 20157
10 20207
11 20146
12 20136
13 20156
14
Detection and Classification of Hard Exudates in Human Retinal Fundus Images Using Clustering and Random Forest Methods
20155
15 20205
16 20155
17 20135
18 20254
19 20144
20 20114

About G. Kavitha

G. Kavitha is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Neurology, Artificial Intelligence and Cognitive Neuroscience, having authored 56 papers that have together received 218 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (16 papers), Brain Tumor Detection and Classification (13 papers), Retinal Imaging and Analysis (6 papers), Digital Imaging for Blood Diseases (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Advanced MRI Techniques and Applications (4 papers). The work is most often cited by research in Health Information Management (24 citations), Computer Vision and Pattern Recognition (105 citations), Neurology (35 citations), Radiology, Nuclear Medicine and Imaging (83 citations) and Media Technology (20 citations). G. Kavitha has collaborated with scholars based in India, United Arab Emirates and Thailand. Frequent co-authors include C. M. Sujatha, V. Natarajan, S. Ramakrishnan, N. Suthanthira Vanitha, V. Vaidehi, Sudha Ramakrishnan, J. Karthikeyan, R. Sıva Subramanıan, Saikat Banerjee and N Aishwarya. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, International Journal of Imaging Systems and Technology, Applied Artificial Intelligence, Measurement and Scientific Reports.

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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