K. Thinakaran

715 total citations
24 papers, 317 citations indexed

About

K. Thinakaran is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, K. Thinakaran has authored 24 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in K. Thinakaran's work include Video Surveillance and Tracking Methods (7 papers), Anomaly Detection Techniques and Applications (4 papers) and Digital Media Forensic Detection (4 papers). K. Thinakaran is often cited by papers focused on Video Surveillance and Tracking Methods (7 papers), Anomaly Detection Techniques and Applications (4 papers) and Digital Media Forensic Detection (4 papers). K. Thinakaran collaborates with scholars based in India, Uzbekistan and Canada. K. Thinakaran's co-authors include T J Nandhini, Syed Noeman Taqui, Dilli Ganesh, M. Adimoolam, Chitapong Wechtaisong, M. Balamurugan, Raju Kannadasan, Arfat Ahmad Khan, M. Nalini and Velmurugan Subbiah Parvathy and has published in prestigious journals such as Electronics, Materials Today Proceedings and International Journal of Electronics and Communication Engineering.

In The Last Decade

K. Thinakaran

17 papers receiving 278 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Thinakaran India 12 92 77 52 33 25 24 317
Mudita Uppal India 11 60 0.7× 49 0.6× 74 1.4× 50 1.5× 20 0.8× 55 290
Ali Akbar Movassagh Iran 5 111 1.2× 59 0.8× 75 1.4× 42 1.3× 14 0.6× 8 277
M. Ilayaraja India 8 122 1.3× 50 0.6× 41 0.8× 81 2.5× 18 0.7× 33 333
G. Nagarajan India 11 94 1.0× 113 1.5× 84 1.6× 59 1.8× 12 0.5× 70 362
Nidhi Sindhwani India 11 57 0.6× 51 0.7× 62 1.2× 36 1.1× 11 0.4× 39 262
Amit Verma India 11 55 0.6× 127 1.6× 22 0.4× 35 1.1× 19 0.8× 44 350
Surendran Rajendran India 10 71 0.8× 33 0.4× 95 1.8× 72 2.2× 13 0.5× 30 336
Md Babul Islam Italy 14 144 1.6× 40 0.5× 26 0.5× 33 1.0× 28 1.1× 33 339
Gurpreet Singh India 9 54 0.6× 46 0.6× 92 1.8× 47 1.4× 12 0.5× 41 256
Aloysius George United States 8 115 1.3× 82 1.1× 56 1.1× 36 1.1× 8 0.3× 11 307

Countries citing papers authored by K. Thinakaran

Since Specialization
Citations

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

Fields of papers citing papers by K. Thinakaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Thinakaran

This figure shows the co-authorship network connecting the top 25 collaborators of K. Thinakaran. A scholar is included among the top collaborators of K. Thinakaran 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 K. Thinakaran. K. Thinakaran 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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Thinakaran, K., et al.. (2024). Deep Learning Technique for Dermoscopy Image Processing Model for Early Melanoma Detection. 909–916. 1 indexed citations
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Thinakaran, K., et al.. (2024). An Adapted Walrus Optimal Routing with Reputation Trust Based Secure Protocol For WSN. International Journal of Electronics and Communication Engineering. 11(1). 101–115.
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Thinakaran, K., et al.. (2024). IoT-Enabled Sleep Monitoring Wearables: Advancements in Tracking and Analysis. 1–5. 1 indexed citations
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Nandhini, T J & K. Thinakaran. (2023). Deep Neural Network-based Crime Scene Detection with Frames. 1–8. 28 indexed citations
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Nandhini, T J & K. Thinakaran. (2023). Detection of Crime Scene Objects using Deep Learning Techniques. 357–361. 44 indexed citations
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Nandhini, T J & K. Thinakaran. (2023). A Robust Framework for Traffic Object Detection using Intelligent Techniques. 328–333. 17 indexed citations
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Nandhini, T J & K. Thinakaran. (2023). Optimizing Forensic Investigation and Security Surveillance with Deep Reinforcement Learning Techniques. 1–5. 15 indexed citations
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Nandhini, T J & K. Thinakaran. (2023). An Improved Crime Scene Detection System Based on Convolutional Neural Networks and Video Surveillance. 1–6. 28 indexed citations
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Thinakaran, K., et al.. (2022). Novel Software Effort Estimation Method using Naive Bayes Technique. 1600–1602. 1 indexed citations
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Adimoolam, M., K. Thinakaran, M. Balamurugan, et al.. (2022). Suspicious Actions Detection System Using Enhanced CNN and Surveillance Video. Electronics. 11(24). 4210–4210. 17 indexed citations
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Nandhini, T J & K. Thinakaran. (2022). CNN Based Moving Object Detection from Surveillance Video in Comparison with GMM. 1–6. 39 indexed citations
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Thinakaran, K., et al.. (2021). AlexNet approach for early stage Alzheimer’s disease detection from MRI brain images. Materials Today Proceedings. 51. 58–65. 37 indexed citations
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Thinakaran, K., et al.. (2021). Efficient Network Resource Allocation Technique for Dynamic IoT Environment using Reinforcement Learning and CAT Optimization. 11799–11815.
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Thinakaran, K., et al.. (2020). Predicting the 2-dimensional airfoil by usingmachine learning methods. 5(3). 291. 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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