Praveen Srinivasan

Computer Vision and Pattern Recognition · 2005–2015

A researcher in the Science corpus: 3 papers; trusts 39 researchers and is trusted by 451 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it; #1,979 of 21,575 by trust here, #3,476 by citations
• Artificial Intelligence — 12 citations into it; #16,258 of 35,345 by trust here, #6,064 by citations
• Computational Mechanics — 7 citations into it

Whom Praveen Srinivasan trusts overall

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

1. Ivan Laptev
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Navneet Dalal
5. Abhinav Kumar Gupta
6. Karen Simonyan
7. Brian Curless
8. Alex Graves
9. Brett Allen
10. Ilya Sutskever

Who trusts Praveen Srinivasan overall

1. Michael J. Black
2. Hossein Rahmani
3. Arjun Jain
4. Jitendra Malik
5. Abhinav Kumar Gupta
6. Davide Boscaini
7. Marcus Rohrbach
8. Hanbyul Joo
9. Angjoo Kanazawa
10. Sara Alexandra Gomes Vicente

Papers from Praveen Srinivasan's perspective

Ordered by how strongly the researchers Praveen Srinivasan 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. Gradient-based learning applied to document recognition
5. Going deeper with convolutions
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• SCAPE: shape completion and animation of people (2005) — 1,984 citations
• Understanding videos, constructing plots learning a visually grounded storyline model from annotated videos (2009) — 299 citations
• Massively Parallel Methods for Deep Reinforcement Learning (2015) — 536 citations