Nima Sedaghat

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 485 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it; #9,864 of 21,575 by trust here, #9,722 by citations
• Artificial Intelligence — 28 citations into it
• 3D Vision & Pose — 14 citations into it; #340 of 689 by trust here, #493 by citations
• Aerospace Engineering — 10 citations into it
• Computational Mechanics — 7 citations into it; #4,027 of 10,001 by trust here, #4,039 by citations
• Geology — 7 citations into it
• Model Architectures — 7 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Nima Sedaghat trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Andrew Zisserman
4. Alex Krizhevsky
5. Kaiming He
6. Jianxiong Xiao
7. Ross B. Girshick
8. Shuran Song
9. Yann LeCun
10. Rob Fergus

Who trusts Nima Sedaghat overall

1. Daniel E. Worrall
2. Martin Simonovsky
3. Zhangjie Cao
4. Chong Xiang
5. Zhizhong Han
6. Carlos Esteves
7. Andrew Brock
8. Xinwei He
9. Miguel Domínguez
10. Gabriel J. Brostow

Papers from Nima Sedaghat's perspective

Ordered by how strongly the researchers Nima Sedaghat 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection (2017) — 225 citations
• Orientation-boosted Voxel Nets for 3D Object Recognition (2016) — 233 citations