S. Malathi

57 papers receiving 641 citations

Peers

S. Malathi
Comparison fields: 5 of 121
  • Signal Processing 73
  • Computer Vision and Pattern Recognition 131
  • Neurology 40
  • Software 21
  • Health Information Management 20
Replace S. Radhika with:
S. Radhika India
Hwanhee Kim South Korea
Deepak Thakur India
Mohamed Kissi Morocco
Han Zhao China
Arushi Jain India
Yongquan Dong China
Aarti Aarti India
Jingjing Yang China
P. Uma Maheswari India
S. Malathi relative to S. Radhika India S. Radhika's profile →
Citations per field
00.5×
S. Radhika · 1×
Citations per year

Countries citing papers authored by S. Malathi

Since Specialization
Citations

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

Fields of papers citing papers by S. Malathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside S. Malathi, 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 S. Malathi Line = papers co-authored together S. Malathi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018167
2 201172
3 202242
4 201336
5 201833
6 202024
7 201023
8 201119
9 202118
10 201918
11 200617
12 201416
13 201415
14 201515
15 201815
16 201014
17 202114
18 201114
19 201213
20 202111

About S. Malathi

S. Malathi is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Information Systems, Electrical and Electronic Engineering and Software, having authored 69 papers that have together received 730 indexed citations. Recurring topics across this work include Biometric Identification and Security (10 papers), Software Engineering Research (7 papers), Software Reliability and Analysis Research (7 papers), Software Engineering Techniques and Practices (5 papers), Brain Tumor Detection and Classification (5 papers), Video Surveillance and Tracking Methods (4 papers), Vehicle License Plate Recognition (3 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Signal Processing (73 citations), Computer Vision and Pattern Recognition (131 citations), Neurology (40 citations), Software (21 citations) and Health Information Management (20 citations). S. Malathi has collaborated with scholars based in India, United States and South Korea. Frequent co-authors include Palani Perumal, V. D. Ambeth Kumar, Sashank Sridhar, Shilpi Agarwal, Vinod Kumar Gupta, Rajeev Jain, Arunima Nayak, Tawfik A. Saleh, S. Balasubramanian and S. Narayana Kalkura. Their work appears in journals such as International Journal of Imaging Systems and Technology, Materials Advances, Sensors International, Indian Journal of Science and Technology and Materials Science and Engineering C.

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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