S. Lokesh

878 total citations · 1 hit paper
41 papers, 391 citations indexed

About

S. Lokesh is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, S. Lokesh has authored 41 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 8 papers in Computer Networks and Communications and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in S. Lokesh's work include Vehicular Ad Hoc Networks (VANETs) (5 papers), IoT and Edge/Fog Computing (4 papers) and COVID-19 diagnosis using AI (4 papers). S. Lokesh is often cited by papers focused on Vehicular Ad Hoc Networks (VANETs) (5 papers), IoT and Edge/Fog Computing (4 papers) and COVID-19 diagnosis using AI (4 papers). S. Lokesh collaborates with scholars based in India and Saudi Arabia. S. Lokesh's co-authors include Gokulnath Chandra Babu, P. Parthasarathy, Priyan Malarvizhi Kumar, R. Varatharajan, Aswathy Ravikumar, Rajesh Kumar, D. Vignesh, P. Chandrasekaran, Kumaravel Selvakumar and K. Murugan and has published in prestigious journals such as Future Generation Computer Systems, Computer Networks and Energy Reports.

In The Last Decade

S. Lokesh

31 papers receiving 359 citations

Hit Papers

align trajectories sort by overperformance

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.

Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier

2018 221 citations S. Lokesh et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. Lokesh India	7	137	99	90	67	63	41	391
Romana Talat Pakistan	5	96 0.7×	56 0.6×	100 1.1×	30 0.4×	43 0.7×	10	316
Majed Aborokbah Saudi Arabia	8	223 1.6×	95 1.0×	180 2.0×	53 0.8×	72 1.1×	33	478
Siddharth Patil United States	6	43 0.3×	53 0.5×	88 1.0×	32 0.5×	58 0.9×	12	382
Debabrata Singh India	10	147 1.1×	41 0.4×	83 0.9×	40 0.6×	42 0.7×	52	375
Devendra Prasad India	15	358 2.6×	61 0.6×	105 1.2×	55 0.8×	49 0.8×	67	592
Chenguang He China	8	151 1.1×	61 0.6×	37 0.4×	25 0.4×	39 0.6×	39	321
Soman KP India	8	159 1.2×	41 0.4×	233 2.6×	61 0.9×	39 0.6×	20	424
S. Balasubramaniam India	11	70 0.5×	38 0.4×	109 1.2×	42 0.6×	19 0.3×	23	278
Ashish Sharma India	7	60 0.4×	83 0.8×	136 1.5×	25 0.4×	67 1.1×	22	405
Md. Mahfuz Reza Bangladesh	8	180 1.3×	126 1.3×	100 1.1×	17 0.3×	63 1.0×	15	426

Countries citing papers authored by S. Lokesh

Since Specialization

Citations

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

Fields of papers citing papers by S. Lokesh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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

All Works

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20 of 20 papers shown

Lokesh, S., et al.. (2026). Network Traffic Prediction Using Integrated Deep Graph Neural Network Based on Big Data. International Journal of Communication Systems. 39(4).

Lokesh, S., et al.. (2025). FinFET Technology Based Development of Energy Efficient Datapath System. 1–6.

Lokesh, S., et al.. (2025). Deep-APT: deep learning based efficient accident prevention technique in fogged environment. Signal Image and Video Processing. 19(5).

Lokesh, S., et al.. (2024). Enhancing Agricultural Decision-Making: A Supervised Machine Learning Approach. 446–453. 1 indexed citations

Lokesh, S., et al.. (2024). Enhanced Lung Cancer Diagnosis and Staging With HRNeT: A Deep Learning Approach. International Journal of Imaging Systems and Technology. 34(6). 1 indexed citations

Selvakumar, Kumaravel & S. Lokesh. (2024). Deep-KEDI: Deep learning-based zigzag generative adversarial network for encryption and decryption of medical images. Technology and Health Care. 32(5). 3231–3251.

Lokesh, S., Kevin France, & Shiyana Eliyas. (2024). Classification of melanoma skin cancer using convolutional neural network. 1–8.

Sreejith, P. S., et al.. (2024). OPEN EYE: An Information Gathering Tool Using OSINT Framework. 1–6. 1 indexed citations

Selvakumar, Kumaravel & S. Lokesh. (2024). A cryptographic method to have a secure communication of health care digital data into the cloud. Automatika. 65(1). 373–386. 2 indexed citations

10.

Lokesh, S., et al.. (2023). Jacobian linear regression and Tate Bryant Euler angle enabled autonomous vehicle LiFi communication sustained IOT. Automatika. 64(4). 1095–1106.

11.

Lokesh, S. & P. Chandrasekaran. (2023). Mechanical and durability performance of sustainable concrete with the inclusion of alternative fine aggregate. Materials Express. 13(1). 147–158. 1 indexed citations

12.

Lokesh, S., et al.. (2023). Spam Detection on Social Media Platform. 10(6). 355–361. 1 indexed citations

13.

Lokesh, S., et al.. (2022). Adaptive scheduled partitioning technique for reliable emergency message broadcasting in VANET for intelligent transportation systems. Automatika. 64(2). 341–354. 10 indexed citations

14.

Ravikumar, Aswathy, et al.. (2022). Effect of neural network structure in accelerating performance and accuracy of a convolutional neural network with GPU/TPU for image analytics. PeerJ Computer Science. 8. e909–e909. 21 indexed citations

15.

Lokesh, S., et al.. (2022). Automatic Image Annotation Using Adaptive Convolutional Deep Learning Model. Intelligent Automation & Soft Computing. 36(1). 481–497. 4 indexed citations

16.

Lokesh, S., et al.. (2020). Remote health and monitoring, heart attack detection and location tracking system with IoT. 1(1). 1–5. 1 indexed citations

17.

Lokesh, S., et al.. (2019). Automatic text summarization. International journal of advance research, ideas and innovations in technology. 5(3). 287–289. 1 indexed citations

18.

Lokesh, S., et al.. (2018). Technologies Enduring in Internet of Medical Things (IoMT) for Smart Healthcare System. International Journal of Scientific Research in Computer Science Engineering and Information Technology. 3(5). 566–572. 1 indexed citations

19.

Lokesh, S., et al.. (2018). Vehicular Cloud Computing Based Intelligent Transportation System for Traffic Management and Road Safety. International Journal of Computer Sciences and Engineering. 6(7). 970–975.

20.

Lokesh, S., et al.. (2018). Vehicular Cloud for Smart Driving Using Internet of Things. Journal of Medical Systems. 42(12). 240–240. 3 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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