Vinoth Kumar Venkatesan

425 total citations · 1 hit paper
9 papers, 238 citations indexed

About

Vinoth Kumar Venkatesan is a scholar working on Neurology, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Vinoth Kumar Venkatesan has authored 9 papers receiving a total of 238 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Neurology, 3 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in Vinoth Kumar Venkatesan's work include Brain Tumor Detection and Classification (4 papers), Artificial Intelligence in Healthcare (2 papers) and AI in cancer detection (2 papers). Vinoth Kumar Venkatesan is often cited by papers focused on Brain Tumor Detection and Classification (4 papers), Artificial Intelligence in Healthcare (2 papers) and AI in cancer detection (2 papers). Vinoth Kumar Venkatesan collaborates with scholars based in India, Ethiopia and Ukraine. Vinoth Kumar Venkatesan's co-authors include Mahesh Thyluru Ramakrishna, Ivan Izonin, C. Rohith Bhat, T R Mahesh, Suresh Guluwadi, Francesco Flammini, H L Gururaj, Roman Tkachenko, Shashi Kant Gupta and Muskan Gupta and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Applied Sciences.

In The Last Decade

Vinoth Kumar Venkatesan

7 papers receiving 232 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Transformative Breast Cancer Diagnosis using CNNs with Optimized ReduceLROnPlateau and Early Stopping Enhancements

2024 54 citations T R Mahesh, Muskan Gupta et al. International Journal of Computational Intelligence Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vinoth Kumar Venkatesan India	6	90	37	35	32	32	9	238
Shakil Ahmed Bangladesh	8	137 1.5×	28 0.8×	23 0.7×	21 0.7×	29 0.9×	14	238
Narayan Vyas India	10	63 0.7×	23 0.6×	39 1.1×	19 0.6×	25 0.8×	31	214
Thulasi Bikku India	8	115 1.3×	30 0.8×	48 1.4×	27 0.8×	26 0.8×	42	244
Stephen Jeswinde Nuagah Ghana	7	81 0.9×	48 1.3×	19 0.5×	76 2.4×	30 0.9×	16	284
Godwin Brown Tunze Tanzania	7	139 1.5×	47 1.3×	12 0.3×	34 1.1×	22 0.7×	8	294
Kamal Kant Hiran India	9	63 0.7×	32 0.9×	20 0.6×	73 2.3×	25 0.8×	23	236
Ranjan Walia India	9	46 0.5×	43 1.2×	15 0.4×	46 1.4×	16 0.5×	37	228
S. Revathy India	8	126 1.4×	61 1.6×	38 1.1×	27 0.8×	29 0.9×	49	297
K. Arumugam India	6	115 1.3×	43 1.2×	80 2.3×	63 2.0×	55 1.7×	12	308
Mudita Uppal India	11	60 0.7×	50 1.4×	22 0.6×	74 2.3×	21 0.7×	55	290

Countries citing papers authored by Vinoth Kumar Venkatesan

Since Specialization

Citations

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

Fields of papers citing papers by Vinoth Kumar Venkatesan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vinoth Kumar Venkatesan. 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 Vinoth Kumar Venkatesan. The network helps show where Vinoth Kumar Venkatesan may publish in the future.

Co-authorship network of co-authors of Vinoth Kumar Venkatesan

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Anitha, J., et al.. (2024). Mapping of soil suitability for medicinal plants using machine learning methods. Scientific Reports. 14(1). 3741–3741. 10 indexed citations

2.

Ramakrishna, Mahesh Thyluru, et al.. (2024). Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification. Computers, materials & continua/Computers, materials & continua (Print). 81(1). 867–883. 1 indexed citations

3.

Chakravarthy, S. R. Sannasi, et al.. (2024). Spatial Attention Integrated EfficientNet Architecture for Breast Cancer Classification with Explainable AI. Computers, materials & continua/Computers, materials & continua (Print). 80(3). 5029–5045. 3 indexed citations

4.

Mahesh, T R, et al.. (2024). Transformative Breast Cancer Diagnosis using CNNs with Optimized ReduceLROnPlateau and Early Stopping Enhancements. International Journal of Computational Intelligence Systems. 17(1). 54 indexed citations breakdown →

5.

Ramakrishna, Mahesh Thyluru, et al.. (2023). HCoF: Hybrid Collaborative Filtering Using Social and Semantic Suggestions for Friend Recommendation. Electronics. 12(6). 1365–1365. 33 indexed citations

6.

Natarajan, Rajesh, et al.. (2023). A Novel Framework on Security and Energy Enhancement Based on Internet of Medical Things for Healthcare 5.0. Infrastructures. 8(2). 22–22. 45 indexed citations

7.

Venkatesan, Vinoth Kumar, et al.. (2023). Efficient Data Preprocessing with Ensemble Machine Learning Technique for the Early Detection of Chronic Kidney Disease. Applied Sciences. 13(5). 2885–2885. 41 indexed citations

8.

Bhat, C. Rohith, et al.. (2023). Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images. SHILAP Revista de lepidopterología. 100–100.

9.

Ramakrishna, Mahesh Thyluru, et al.. (2023). Homogeneous Adaboost Ensemble Machine Learning Algorithms with Reduced Entropy on Balanced Data. Entropy. 25(2). 245–245. 51 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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