S. Prabha

647 total citations
49 papers, 278 citations indexed

About

S. Prabha is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Neurology. According to data from OpenAlex, S. Prabha has authored 49 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Computer Vision and Pattern Recognition and 10 papers in Neurology. Recurrent topics in S. Prabha's work include Brain Tumor Detection and Classification (10 papers), Retinal Imaging and Analysis (9 papers) and AI in cancer detection (6 papers). S. Prabha is often cited by papers focused on Brain Tumor Detection and Classification (10 papers), Retinal Imaging and Analysis (9 papers) and AI in cancer detection (6 papers). S. Prabha collaborates with scholars based in India, Malaysia and United States. S. Prabha's co-authors include C. M. Sujatha, K. Sakthidasan Sankaran, Ramakrishnan Swaminathan, K. Vijayakumar, M. Sasikala, R. Geetha, Peeta Basa Pati, V. Rajinikanth, Ramya Mohan and N. Balaji and has published in prestigious journals such as Applied Soft Computing, Neural Computing and Applications and International Journal of Neuroscience.

In The Last Decade

S. Prabha

36 papers receiving 264 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Prabha India 10 113 96 72 62 50 49 278
Mikhail Belyaev Russia 6 169 1.5× 88 0.9× 146 2.0× 88 1.4× 27 0.5× 18 360
Akshay Aggarwal India 6 209 1.8× 52 0.5× 149 2.1× 84 1.4× 58 1.2× 16 357
Xinyan Zhao China 5 123 1.1× 39 0.4× 110 1.5× 66 1.1× 39 0.8× 9 313
Saravanan Srinivasan India 11 157 1.4× 86 0.9× 127 1.8× 121 2.0× 27 0.5× 22 388
Tongtong Che China 11 44 0.4× 146 1.5× 68 0.9× 67 1.1× 11 0.2× 22 313
Hossam El-Din Moustafa Egypt 12 223 2.0× 159 1.7× 220 3.1× 110 1.8× 110 2.2× 56 536
Jundong Liu United States 9 64 0.6× 49 0.5× 95 1.3× 196 3.2× 13 0.3× 35 362
Rajeswari India 5 125 1.1× 37 0.4× 67 0.9× 67 1.1× 51 1.0× 19 252
Jonathan Stoeckel United States 6 86 0.8× 112 1.2× 83 1.2× 111 1.8× 21 0.4× 11 339
M. Satya Sai Ram India 7 164 1.5× 43 0.4× 86 1.2× 82 1.3× 50 1.0× 40 276

Countries citing papers authored by S. Prabha

Since Specialization
Citations

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

Fields of papers citing papers by S. Prabha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Prabha

This figure shows the co-authorship network connecting the top 25 collaborators of S. Prabha. A scholar is included among the top collaborators of S. Prabha 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 S. Prabha. S. Prabha 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
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Vijayakumar, K., et al.. (2024). Classification of Chest Radiographs into Normal and Pneumonia Class Using Fused Deep-Features. 1–6. 1 indexed citations
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Prabha, S., et al.. (2024). Automatic Classification of Healthy/TB Chest X-ray using DeepLearning. 1–5. 12 indexed citations
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Prabha, S., et al.. (2024). Forest Region Extraction and Evaluation from Satellite Images using CNN Segmentation. 1–5. 4 indexed citations
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Vijayakumar, K., et al.. (2024). Deep Transfer-Learning Assisted Healthy/Disease Strawberry Leaf Images Classification. 1–5. 3 indexed citations
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Vijayakumar, K., et al.. (2024). Deep-Learning and Geometric Mean Optimizer Combined Scheme for Brain MRI Classification. 1–6. 1 indexed citations
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Prabha, S., et al.. (2023). Auto-grading C programming assignments with CodeBERT and Random Forest Regressor. 1–6. 9 indexed citations
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Prabha, S., et al.. (2022). Improving Performance Of Next.Js App And Testing It While Building A Badminton Based Web App. SSRN Electronic Journal. 2 indexed citations
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Prabha, S., et al.. (2022). Survey on Structural Neuro Imaging for the Identification of BrainAbnormalities in Schizophrenia. Current Medical Imaging Formerly Current Medical Imaging Reviews. 19(2). 115–125. 1 indexed citations
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Prabha, S.. (2019). Thermal Imaging Techniques for Breast Screening - A Survey. Current Medical Imaging Formerly Current Medical Imaging Reviews. 16(7). 855–862. 7 indexed citations
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Prabha, S., et al.. (2018). Brain Hemisphere Analysis Using Genetic Algorithm and Fuzzy Clustering in Alzheimer Disease. 4. 901–905. 4 indexed citations
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Sankaran, K. Sakthidasan, S. Prabha, & P. M. Rubesh Anand. (2018). Optimized gradient histogram preservation with block wise SURE shrinkage for noise free image restoration. Cluster Computing. 22(S2). 4457–4478. 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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