Pavan K. Turaga

Computer Vision and Pattern Recognition · 2008–2018

A researcher in the Science corpus: 10 papers; trusts 509 researchers and is trusted by 83 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 149 citations into it; #3,515 of 21,575 by trust here, #3,393 by citations
• Artificial Intelligence — 44 citations into it; #6,729 of 35,345 by trust here, #5,028 by citations
• Computational Mechanics — 28 citations into it; #4,415 of 10,001 by trust here, #2,203 by citations
• Signal Processing — 23 citations into it
• Biomedical Engineering — 20 citations into it; #951 of 10,734 by trust here, #1,348 by citations
• Media Technology — 20 citations into it; #3,046 of 3,621 by trust here, #3,318 by citations
• Representation & Self-Supervised Learning — 19 citations into it; #2,366 of 3,145 by trust here, #2,404 by citations
• Geometry and Topology — 18 citations into it; #4,431 of 7,422 by trust here, #2,475 by citations

Whom Pavan K. Turaga trusts overall

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

1. Geoffrey E. Hinton
2. Gianfranco Doretto
3. Alex Krizhevsky
4. Ivan Laptev
5. Kaiming He
6. Ross B. Girshick
7. Diederik P. Kingma
8. Yoshua Bengio
9. Sam T. Roweis
10. Yann LeCun

Who trusts Pavan K. Turaga overall

1. Rim Slama
2. Zhiwu Huang
3. Hazem Wannous
4. Michael S. Ryoo
5. Xiongtao Dai
6. Yueng Santiago Delahoz
7. Mohamed Daoudi
8. Christoph Feichtenhofer
9. Michalis Vrigkas
10. Du Tran

Papers from Pavan K. Turaga's perspective

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

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

Their papers

• Machine Recognition of Human Activities: A Survey (2008) — 1,524 citations
• Moving vistas: Exploiting motion for describing scenes (2010) — 100 citations
• Statistical Computations on Grassmann and Stiefel Manifolds for Image and Video-Based Recognition (2011) — 402 citations
• A Blur-Robust Descriptor with Applications to Face Recognition (2012) — 98 citations
• ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements (2016) — 714 citations
• Locally time-invariant models of human activities using trajectories on the grassmannian (2009) — 63 citations
• Domain Adaptive Dictionary Learning (2012) — 152 citations
• Elastic functional coding of human actions: From vector-fields to latent variables (2015) — 96 citations
• Shading prediction, fault detection, and consensus estimation for solar array control (2018) — 24 citations
• Elastic Functional Coding of Riemannian Trajectories (2016) — 54 citations