H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 45 Citations 20,072 113 World Ranking 3600 National Ranking 162

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

Artificial intelligence, Computer vision, Mean-shift, Robustness and Bhattacharyya distance are his primary areas of study. His study explores the link between Artificial intelligence and topics such as Pattern recognition that cross with problems in Kalman filter. His work on Object, Face, Video tracking and Change detection as part of general Computer vision study is frequently linked to Motion detection, bridging the gap between disciplines.

His Mean-shift research is multidisciplinary, incorporating perspectives in Nonparametric statistics, Kernel, Convergence, Estimator and Mathematical optimization. His Bhattacharyya distance research incorporates themes from Similarity measure and Kernel. His Kernel research is multidisciplinary, incorporating elements of Histogram, Facial motion capture, Position and Metric.

His most cited work include:

  • Kernel-based object tracking (4322 citations)
  • Real-time tracking of non-rigid objects using mean shift (2814 citations)
  • The variable bandwidth mean shift and data-driven scale selection (394 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Machine learning. Object, Object detection, Change detection, Video tracking and Face detection are the subjects of his Computer vision studies. His Pattern recognition study combines topics from a wide range of disciplines, such as Background subtraction, Data mining, Feature and Mean-shift.

Visvanathan Ramesh interconnects Bhattacharyya distance and Cluster analysis in the investigation of issues within Mean-shift. The Algorithm study combines topics in areas such as Covariance and Mathematical optimization. His Machine learning research is multidisciplinary, relying on both Generative model and Rendering.

He most often published in these fields:

  • Artificial intelligence (76.71%)
  • Computer vision (43.84%)
  • Pattern recognition (23.29%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (76.71%)
  • Machine learning (13.01%)
  • Artificial neural network (8.22%)

In recent papers he was focusing on the following fields of study:

Visvanathan Ramesh mainly investigates Artificial intelligence, Machine learning, Artificial neural network, Convolutional neural network and Rendering. His work carried out in the field of Artificial intelligence brings together such families of science as Multimedia and Computer vision. His study in the fields of Virtual image under the domain of Computer vision overlaps with other disciplines such as Signal transition.

Visvanathan Ramesh combines subjects such as Open set, Probabilistic logic, Generative model and Linear classifier with his study of Machine learning. The various areas that Visvanathan Ramesh examines in his Artificial neural network study include Statistics and Metric. His work deals with themes such as Object detection, Ground truth and Graphics, which intersect with Rendering.

Between 2014 and 2021, his most popular works were:

  • A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning. (14 citations)
  • Model-driven Simulations for Deep Convolutional Neural Networks. (11 citations)
  • Model Validation for Vision Systems via Graphics Simulation. (8 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Statistics

Visvanathan Ramesh mainly focuses on Machine learning, Artificial intelligence, Rendering, Convolutional neural network and Deep learning. The study incorporates disciplines such as Probabilistic logic, Fidelity and Graphics in addition to Machine learning. His research integrates issues of Data modeling, Computer graphics and Machine vision in his study of Fidelity.

Visvanathan Ramesh has included themes like Open set and Parametric statistics in his Artificial intelligence study. His Open set research integrates issues from Encoder, Generative model, Linear classifier and Bayesian inference. His Test set study incorporates themes from Field, Active learning and Identification.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Kernel-based object tracking

D. Comaniciu;V. Ramesh;P. Meer.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

6685 Citations

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

D. Comaniciu;V. Ramesh;P. Meer.
computer vision and pattern recognition (2000)

4597 Citations

The variable bandwidth mean shift and data-driven scale selection

D. Comaniciu;V. Ramesh;P. Meer.
international conference on computer vision (2001)

667 Citations

Background modeling and subtraction of dynamic scenes

Monnet;Mittal;Paragios;Visvanathan Ramesh.
international conference on computer vision (2003)

586 Citations

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

C. Bahlmann;Y. Zhu;Visvanathan Ramesh;M. Pellkofer.
intelligent vehicles symposium (2005)

569 Citations

Gradient vector flow fast geodesic active contours

N. Paragios;O. Mellina-Gottardo;V. Ramesh.
international conference on computer vision (2001)

425 Citations

Gradient vector flow fast geometric active contours

N. Paragios;O. Mellina-Gottardo;V. Ramesh.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

401 Citations

Mean shift and optimal prediction for efficient object tracking

D. Comaniciu;V. Ramesh.
international conference on image processing (2000)

353 Citations

Statistical calibration of CCD imaging process

Y. Tsin;V. Ramesh;T. Kanade.
international conference on computer vision (2001)

330 Citations

Topology free hidden Markov models: application to background modeling

B. Stenger;V. Ramesh;N. Paragios;F. Coetzee.
international conference on computer vision (2001)

320 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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