M. Suganthi

450 citations
48 papers · 324 · h-index 10

Impact in

Papers in

M. Suganthi

42 papers receiving 289 citations

Peers

M. Suganthi
Comparison fields: 5 of 59
  • Neurology 60
  • Health Informatics 9
  • Computer Vision and Pattern Recognition 113
  • Computer Networks and Communications 95
  • Artificial Intelligence 133
Replace Eid Rehman with:
Eid Rehman Pakistan
Murat Canayaz Türkiye
Amir Hanif Dar Pakistan
Ashutosh Aggarwal India
C. Balasubramanian India
Shailendra Tiwari India
K. Venkatalakshmi India
K. Gunavathi India
Ramdas Vankdothu India
M. Suganthi relative to Eid Rehman Pakistan Eid Rehman's profile →
Citations per field
00.5×2.8×
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Citations per year

Countries citing papers authored by M. Suganthi

Since Specialization
Citations

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

Fields of papers citing papers by M. Suganthi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside M. Suganthi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Suganthi Line = papers co-authored together M. Suganthi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201042
2 201934
3 201832
4 201622
5 201820
6 201819
7 200915
8 202012
9 201911
10 20169
11 20198
12 20097
13 20107
14
Mammogram tumor classification using multimodal features and Genetic Algorithm
20096
15 20116
16 20116
17 20075
18 20105
19 20184
20 20184

About M. Suganthi

M. Suganthi is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology, having authored 48 papers that have together received 324 indexed citations. Recurring topics across this work include Wireless Communication Networks Research (9 papers), Advanced MIMO Systems Optimization (8 papers), Brain Tumor Detection and Classification (8 papers), AI in cancer detection (7 papers), Cognitive Radio Networks and Spectrum Sensing (6 papers), Energy Efficient Wireless Sensor Networks (6 papers), Opportunistic and Delay-Tolerant Networks (5 papers) and Advanced Wireless Communication Techniques (5 papers). The work is most often cited by research in Neurology (60 citations), Health Informatics (9 citations), Computer Vision and Pattern Recognition (113 citations), Computer Networks and Communications (95 citations) and Artificial Intelligence (133 citations). M. Suganthi has collaborated with scholars based in India, Nepal and United States. Frequent co-authors include M. Madheswaran, S. Kumarganesh, C. Karthikeyan, Shitharth Selvarajan, S. Raghavan, R. Sunder, S. S. Karthikeyan, R. Sumathi, N. Santhiyakumari and S. Umamaheswari. Their work appears in journals such as Journal of Medical Systems, Wireless Personal Communications, International Journal of Bio-Inspired Computation, Pattern Analysis and Applications and International Journal of Imaging Systems and Technology.

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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