Sukumar Letchmunan

1.1k total citations
48 papers, 594 citations indexed

About

Sukumar Letchmunan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Sukumar Letchmunan has authored 48 papers receiving a total of 594 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 12 papers in Information Systems. Recurrent topics in Sukumar Letchmunan's work include Multi-Criteria Decision Making (10 papers), Anomaly Detection Techniques and Applications (7 papers) and Face and Expression Recognition (5 papers). Sukumar Letchmunan is often cited by papers focused on Multi-Criteria Decision Making (10 papers), Anomaly Detection Techniques and Applications (7 papers) and Face and Expression Recognition (5 papers). Sukumar Letchmunan collaborates with scholars based in Malaysia, China and Pakistan. Sukumar Letchmunan's co-authors include Zhe Liu, Umair Muneer Butt, Fadratul Hafinaz Hassan, Hafiz Husnain Raza Sherazi, Anees Baqir, Mubashir Ali, Ai Ping Teoh, Yu–N Cheah, Toqir A. Rana and Muhammet Deveci and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Sukumar Letchmunan

40 papers receiving 566 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sukumar Letchmunan Malaysia 13 261 107 106 91 88 48 594
Devendra K. Tayal India 14 363 1.4× 44 0.4× 65 0.6× 26 0.3× 178 2.0× 75 623
Seppo Puuronen Finland 14 472 1.8× 123 1.1× 54 0.5× 30 0.3× 156 1.8× 51 755
Carla Vairetti Chile 12 345 1.3× 45 0.4× 46 0.4× 52 0.6× 83 0.9× 27 629
Rommel N. Carvalho Brazil 13 345 1.3× 33 0.3× 109 1.0× 39 0.4× 140 1.6× 49 655
Hamidah Ibrahim Malaysia 14 327 1.3× 76 0.7× 193 1.8× 20 0.2× 356 4.0× 190 1.1k
Max Bramer United Kingdom 12 354 1.4× 48 0.4× 51 0.5× 29 0.3× 192 2.2× 69 668
María A. Martínez Spain 10 315 1.2× 34 0.3× 285 2.7× 34 0.4× 184 2.1× 26 816
Tomasz Kajdanowicz Poland 17 424 1.6× 97 0.9× 49 0.5× 16 0.2× 189 2.1× 54 863
Indranil Bose India 8 460 1.8× 56 0.5× 148 1.4× 21 0.2× 132 1.5× 21 824
Erik M. Fredericks United States 10 261 1.0× 38 0.4× 82 0.8× 21 0.2× 149 1.7× 27 593

Countries citing papers authored by Sukumar Letchmunan

Since Specialization
Citations

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

Fields of papers citing papers by Sukumar Letchmunan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sukumar Letchmunan

This figure shows the co-authorship network connecting the top 25 collaborators of Sukumar Letchmunan. A scholar is included among the top collaborators of Sukumar Letchmunan 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 Sukumar Letchmunan. Sukumar Letchmunan 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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Liu, Zhe, et al.. (2025). L2-regularization based two-way weighted neutrosophic clustering with Manhattan and Euclidean distances. Fuzzy Sets and Systems. 518. 109507–109507.
4.
Liu, Zhe, et al.. (2025). Robust multi-view fuzzy clustering with exponential transformation and automatic view weighting. Knowledge-Based Systems. 315. 113314–113314. 1 indexed citations
5.
Liu, Zhe, et al.. (2025). Assessing sustainable energy systems using interval-valued Fermatean fuzzy sets-based decision-making model. Applied Soft Computing. 186. 114261–114261.
6.
Liu, Zhe, Donglai Wang, Sukumar Letchmunan, Kai Liu, & Yulong Huang. (2025). Applications of interval-valued pythagorean fuzzy trigonometric similarity measures in multicriteria decision-making and medical diagnosis. International Journal of Knowledge-based and Intelligent Engineering Systems.
7.
Liu, Zhe, Sukumar Letchmunan, Muhammet Deveci, Tapan Senapati, & Dragan Pamucar. (2025). Integrated decision support model for selection of industrial wastewater treatment technologies. Expert Systems with Applications. 287. 127880–127880. 3 indexed citations
8.
Letchmunan, Sukumar, et al.. (2025). A systematic literature review of lightweight YOLO models for object detection. PeerJ Computer Science. 11. e3357–e3357.
9.
Liu, Zhe, et al.. (2024). Multi-view evidential c-means clustering with view-weight and feature-weight learning. Fuzzy Sets and Systems. 498. 109135–109135. 11 indexed citations
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Liu, Zhe, et al.. (2024). Adaptive weighted multi-view evidential clustering with feature preference. Knowledge-Based Systems. 294. 111770–111770. 33 indexed citations
12.
Liu, Zhe & Sukumar Letchmunan. (2024). An Improved Weighted Evidence Combination Based on Tangent Similarity and Its Application in Decision-Making. 1. 38–50. 6 indexed citations
13.
Osman, Mohd Hafeez, et al.. (2023). Diversity-based Test Case Prioritization Technique to Improve Faults Detection Rate. International Journal of Advanced Computer Science and Applications. 14(6). 2 indexed citations
14.
Butt, Umair Muneer, et al.. (2023). Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI. Computers, materials & continua/Computers, materials & continua (Print). 76(2). 2551–2570. 3 indexed citations
15.
Butt, Umair Muneer, et al.. (2022). Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy. PLoS ONE. 17(9). e0274172–e0274172. 7 indexed citations
16.
Letchmunan, Sukumar, et al.. (2021). Analysis of Deep Neural Networks for Human Activity Recognition in Videos—A Systematic Literature Review. IEEE Access. 9. 126366–126387. 23 indexed citations
17.
Butt, Umair Muneer, Sukumar Letchmunan, Fadratul Hafinaz Hassan, et al.. (2021). Spatio-Temporal Crime Predictions by Leveraging Artificial Intelligence for Citizens Security in Smart Cities. IEEE Access. 9. 47516–47529. 32 indexed citations
18.
Sukumar, Arun, et al.. (2019). IMPROVING CLINIC QUEUES IN MALAYSIA USING TIME-SERIES EXTRAPOLATION FORECAST AND WEB-BASED APPOINTMENT. 8(9). 2 indexed citations
19.
Rana, Toqir A., Yu–N Cheah, & Sukumar Letchmunan. (2016). Topic Modeling in Sentiment Analysis: A Systematic Review. SHILAP Revista de lepidopterología. 10(1). 76–93. 45 indexed citations
20.
Letchmunan, Sukumar, et al.. (2016). Service network security management (SNSM) framework, a solution to SOSE security challenge. 228–233. 1 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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2026