M. Monica Subashini

1.3k citations
60 papers · 865 indexed · h-index 12
Topics
Advanced Neural Network Applications (10 papers)Wireless Body Area Networks (8 papers)Brain Tumor Detection and Classification (8 papers)

In The Last Decade

M. Monica Subashini

49 papers receiving 814 citations

Peers

M. Monica Subashini
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 387
  • Neurology 327
  • Artificial Intelligence 201
  • Cognitive Neuroscience 154
  • Radiology, Nuclear Medicine and Imaging 140
Replace Taha H. Rassem with:
Taha H. Rassem Malaysia
Ali Wali Tunisia
K. Swaraja India
Xujing Yao United Kingdom
Allam Jaya Prakash India
Sangseok Yun South Korea
Cem Direkoğlu Türkiye
Muhammad Awais United Kingdom
Tongguang Ni China
Saeeda Naz Pakistan
M. Monica Subashini relative to Taha H. Rassem Malaysia Taha H. Rassem's profile →
Citations per field
00.5×1.5×
Taha H. Rassem · 1×
Citations per year

Countries citing papers authored by M. Monica Subashini

Since Specialization
Citations

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

Fields of papers citing papers by M. Monica Subashini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Monica Subashini

This figure shows the co-authorship network connecting the top 25 collaborators of M. Monica Subashini. A scholar is included among the top collaborators of M. Monica Subashini 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 M. Monica Subashini. M. Monica Subashini 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
#WorkIndexed citations
1 0
2 10
3 3
4 0
5 0
6 1
7 5
8 1
9 53
10 73
11 0
12 24
13 10
14 2
15 9
16 289
17 2
18 74
19 92
20 0

About M. Monica Subashini

M. Monica Subashini is a scholar working on Computer Vision and Pattern Recognition, Neurology and Media Technology, having authored 60 papers that have together received 865 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (10 papers), Wireless Body Area Networks (8 papers) and Brain Tumor Detection and Classification (8 papers). The work is most often cited by research in Neurology (327 citations), Computer Vision and Pattern Recognition (387 citations) and Media Technology (84 citations). M. Monica Subashini has collaborated with scholars based in India, United Arab Emirates and Malaysia. Frequent co-authors include Geethu Mohan, K. K. Mujeeb Rahman, Sarat Kumar Sahoo, Utkarsh Raj, R Karthik, Venkata Lakshmi Narayana Komanapalli, Umashankar Subramaniam, Alagar Karthick, Dhafer Almakhles and P. Ashok. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Journal of Autism and Developmental Disorders.

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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