K. Shankar

11.0k citations
206 papers · 6.5k indexed · 4 hit papers · h-index 47
Topics
IoT and Edge/Fog Computing (23 papers)Artificial Intelligence in Healthcare (15 papers)Brain Tumor Detection and Classification (15 papers)
Journals
SHILAP Revista de lepidopterologíaJournal of Cleaner ProductionScientific Reports
Partner nations
IndiaVietnamEgypt

In The Last Decade

K. Shankar

190 papers receiving 5.9k citations

Hit Papers

Optimal deep learning model for classification of lung ca...20182026202020232018202120182018100200300

Peers

K. Shankar
Comparison fields: 5 of 172
  • Artificial Intelligence 2.1k
  • Computer Networks and Communications 1.8k
  • Information Systems 1.5k
  • Computer Vision and Pattern Recognition 1.4k
  • Radiology, Nuclear Medicine and Imaging 1.2k
Replace Gunasekaran Manogaran with:
Gunasekaran Manogaran United States
Mohamed Elhoseny Egypt
Gaurav Dhiman India
Praveen Kumar Reddy Maddikunta India
Mehedi Masud Saudi Arabia
Mazin Abed Mohammed Iraq
N. Z. Jhanjhi Malaysia
Deepak Gupta India
Prayag Tiwari China
Chinmay Chakraborty India
K. Shankar relative to Gunasekaran Manogaran United States Gunasekaran Manogaran's profile →
Citations per field
00.5×2.7×
Gunasekaran Manogaran · 1×
Citations per year

Countries citing papers authored by K. Shankar

Since Specialization
Citations

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

Fields of papers citing papers by K. Shankar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

This figure shows the co-authorship network connecting the top 25 collaborators of K. Shankar. A scholar is included among the top collaborators of K. Shankar 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. Shankar. K. Shankar 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 6
2 1
3 5
4 0
5 5
6 19
7 1
8 1
9 5
10 0
11 2
12 1
13 2
14 12
15 1
16 1
17 1
18 8
19 7
20 108

About K. Shankar

K. Shankar is a scholar working on Health Information Management, Computer Vision and Pattern Recognition and Information Systems, having authored 206 papers that have together received 6.5k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (23 papers), Artificial Intelligence in Healthcare (15 papers) and Brain Tumor Detection and Classification (15 papers). The work is most often cited by research in Health Information Management (505 citations), Computer Networks and Communications (1.8k citations) and Computer Vision and Pattern Recognition (1.4k citations). K. Shankar has collaborated with scholars based in India, Vietnam and Egypt. Frequent co-authors include Mohamed Elhoseny, Deepak Gupta, S. K. Lakshmanaprabu, Ashish Khanna, Denis A. Pustokhin, Irina V. Pustokhina, Sachi Nandan Mohanty, J. Uthayakumar, E. Laxmi Lydia and Eswaran Perumal. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Scientific Reports.

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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