Visvanathan Ramesh

Artificial Intelligence · 2000–2020

A researcher in the Science corpus: 7 papers; trusts 456 researchers and is trusted by 1,320 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 161 citations into it; #20,098 of 35,345 by trust here, #17,412 by citations
• Computer Vision and Pattern Recognition — 143 citations into it; #1,143 of 21,575 by trust here, #2,768 by citations
• Representation & Self-Supervised Learning — 45 citations into it
• Meta & Continual Learning — 43 citations into it
• Generative Models — 27 citations into it
• Optimization & Training — 25 citations into it
• Probabilistic & Bayesian Methods — 18 citations into it
• Safety, Robustness & Interpretability — 17 citations into it

Whom Visvanathan Ramesh trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Kaiming He
5. Yann LeCun
6. Yoshua Bengio
7. Paul A. Viola
8. Alex Graves
9. Ilya Sutskever
10. Max Welling

Who trusts Visvanathan Ramesh overall

1. Bastian Leibe
2. Robert T. Collins
3. Dorin Comaniciu
4. Luc Van Gool
5. Xue Mei
6. Ming-Hsuan Yang
7. Konrad Schindler
8. Patrick Pérez
9. Yi Wu
10. Alper Yilmaz

Papers from Visvanathan Ramesh's perspective

Ordered by how strongly the researchers Visvanathan Ramesh trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Real-time tracking of non-rigid objects using mean shift (2000) — 3,395 citations
• Kernel-Based Object Tracking (2003) — 5,099 citations
• The variable bandwidth mean shift and data-driven scale selection (2001) — 503 citations
• Background modeling and subtraction of dynamic scenes (2003) — 482 citations
• A system for traffic sign detection, tracking, and recognition using color, shape, and motion information (2005) — 504 citations
• A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning (2020) — 183 citations
• Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition (2019) — 43 citations