2026 Visvanathan Ramesh: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	51	5203	5060	240	233	146	21669

Visvanathan Ramesh publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Visvanathan Ramesh sits on this spectrum.

32 publications 991+

This scientist: 146 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Visvanathan Ramesh D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Visvanathan Ramesh sits on this spectrum.

30 D-Index 131+

This scientist: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Visvanathan Ramesh is affiliated with Goethe University Frankfurt in Germany. Their research activity spans multiple domains within computer science and engineering, with a focus on artificial intelligence and structural engineering.

Their work primarily addresses topics related to domain adaptation and few-shot learning, neural networks and applications, machine learning and algorithms, and generative adversarial networks and image synthesis. Additional areas of interest include infrastructure maintenance and monitoring, cell image analysis techniques, and human pose and action recognition.

Visvanathan Ramesh has contributed extensively to the body of academic knowledge through numerous publications. These include:

A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning (2023, Neural Networks)
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition (2022, Journal of Imaging)
Chronic within-hive video recordings detect altered nursing behaviour and retarded larval development of neonicotinoid treated honey bees (2020, Scientific Reports)
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning (2020, arXiv (Cornell University))
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning (2021, arXiv (Cornell University))

Their publication record includes frequent contributions to venues such as arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), Neural Networks, Journal of Imaging, and Scientific Reports. Most of the papers have appeared in arXiv, which houses a significant portion of their research output.

Visvanathan Ramesh often collaborates with other researchers. Frequent co-authors include:

Martin Mundt
Iuliia Pliushch
Achref Jaziri
Timm Hess
Andres Fernandez Rodriguez

Their main fields of study consolidate a strong background in computer science, with thirty-two publications, alongside engineering, with twenty publications. Subfields represented in their research include artificial intelligence, civil and structural engineering, computer vision and pattern recognition, biophysics, and plant science.

Best Publications

Kernel-based object tracking

D. Comaniciu;V. Ramesh;P. Meer

7245
Citations
Real-time tracking of non-rigid objects using mean shift

D. Comaniciu;V. Ramesh;P. Meer

5021
Citations
The variable bandwidth mean shift and data-driven scale selection

D. Comaniciu;V. Ramesh;P. Meer

702
Citations
A system for traffic sign detection, tracking, and recognition using color, shape, and motion information

C. Bahlmann;Y. Zhu;Visvanathan Ramesh;M. Pellkofer

650
Citations
Background modeling and subtraction of dynamic scenes

Monnet;Mittal;Paragios;Visvanathan Ramesh

607
Citations
Gradient vector flow fast geodesic active contours

N. Paragios;O. Mellina-Gottardo;V. Ramesh

433
Citations
Gradient vector flow fast geometric active contours

N. Paragios;O. Mellina-Gottardo;V. Ramesh

403
Citations
Mean shift and optimal prediction for efficient object tracking

D. Comaniciu;V. Ramesh

377
Citations
Statistical calibration of CCD imaging process

Y. Tsin;V. Ramesh;T. Kanade

360
Citations
A MRF-based approach for real-time subway monitoring

N. Paragios;V. Ramesh

336
Citations
Topology free hidden Markov models: application to background modeling

B. Stenger;V. Ramesh;N. Paragios;F. Coetzee

328
Citations
Statistical modeling and performance characterization of a real-time dual camera surveillance system

M. Greiffenhagen;V. Ramesh;D. Comaniciu;H. Niemann

266
Citations
Error analysis of background adaption

Xiang Gao;T.E. Boult;F. Coetzee;V. Ramesh

201
Citations
Non-rigid registration using distance functions

Nikos Paragios;Mikael Rousson;Visvanathan Ramesh

200
Citations
System and method for gesture interface

Che-Bin Liu;Visvanathan Ramesh;Bernhard Geiger

191
Citations
Special issue on video communications, processing, and understanding for third generation surveillance systems

Carlo S. Regazzoni;Visvanathan Ramesh;Gian Luca Foresti

182
Citations
Robust detection and tracking of human faces with an active camera

D. Comaniciu;V. Ramesh

174
Citations
Matching Distance Functions: A Shape-to-Area Variational Approach for Global-to-Local Registration

Nikos Paragios;Mikael Rousson;Visvanathan Ramesh

172
Citations
Real-time video object generation for smart cameras

Dorin Comaniciu;Alessio Del Bue;Visvanathan Ramesh

169
Citations
Adaptive resolution system and method for providing efficient low bit rate transmission of image data for distributed applications

Dorin Comaniciu;Visvanathan Ramesh;Fabio Berton

166
Citations

Frequent Co-Authors

Dorin Comaniciu Siemens (United States)

Terrance E. Boult University of Colorado Colorado Springs

Robert M. Haralick City University of New York

Arun Krishnan Microsoft (United States)

Nikos Paragios CentraleSupélec

Peter Meer Rutgers, The State University of New Jersey

Nassir Navab Technical University of Munich

Richard Szeliski University of Washington

Larry S. Davis University of Maryland, College Park

Carlo S. Regazzoni University of Genoa

External Links

Google Scholar page

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