Mohan Shankar

609 citations
16 papers · 470 · h-index 7

Impact in

Papers in

Mohan Shankar

15 papers receiving 433 citations

Peers

Mohan Shankar
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 161
  • Electrical and Electronic Engineering 300
  • Acoustics and Ultrasonics 4
  • Instrumentation 15
  • Biomedical Engineering 186
Replace Sangjun Park with:
Sangjun Park South Korea
Lorenzo Cozzella Italy
Ginés Doménech‐Asensi Spain
Dong-Su Lee South Korea
Hyok Jae Song United States
Yafei Lü China
Hao Yan China
Zhiwei Zhong China
Qiao Sun China
Feng Hong Yang China
Mohan Shankar relative to Sangjun Park South Korea Sangjun Park's profile →
Citations per field
00.5×2×3×4.1×
Sangjun Park · 1×
Citations per year

Countries citing papers authored by Mohan Shankar

Since Specialization
Citations

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

Fields of papers citing papers by Mohan Shankar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Mohan Shankar, 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 Mohan Shankar Line = papers co-authored together Mohan Shankar links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2006145
2 2006116
3 200866
4 200665
5 200624
6 201020
7 200610
8 20236
9 20054
10 20204
11 20243
12 20082
13 20052
14 20191
15 20191
16 20041

About Mohan Shankar

Mohan Shankar is a scholar working on Global and Planetary Change, Aerospace Engineering, Instrumentation, Computer Vision and Pattern Recognition and Biophysics, having authored 16 papers that have together received 470 indexed citations. Recurring topics across this work include Infrared Target Detection Methodologies (4 papers), IoT-based Smart Home Systems (3 papers), Adaptive optics and wavefront sensing (3 papers), Atmospheric Ozone and Climate (3 papers), Atmospheric aerosols and clouds (3 papers), Atmospheric and Environmental Gas Dynamics (3 papers), Calibration and Measurement Techniques (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (161 citations), Electrical and Electronic Engineering (300 citations), Acoustics and Ultrasonics (4 citations), Instrumentation (15 citations) and Biomedical Engineering (186 citations). Mohan Shankar has collaborated with scholars based in United States, India and Taiwan. Frequent co-authors include David J. Brady, B. D. Guenther, Qi Hao, Nikos P. Pitsianis, Steve A. Feller, Ken Yuh Hsu, Robert C. Gibbons, Rebecca M. Willett, Timothy J. Schulz and Caihua Chen. Their work appears in journals such as Applied Optics, Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, Optics Express and IEEE Sensors Journal.

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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