Nam N. Vo

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 552 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 71 citations into it; #5,394 of 21,575 by trust here, #12,419 by citations
• Representation & Self-Supervised Learning — 19 citations into it
• Artificial Intelligence — 18 citations into it; #17,932 of 35,345 by trust here, #27,551 by citations
• Aerospace Engineering — 17 citations into it; #1,061 of 6,421 by trust here, #3,764 by citations
• Media Technology — 11 citations into it
• Model Architectures — 9 citations into it
• Information Retrieval & Search — 7 citations into it
• Signal Processing — 7 citations into it

Whom Nam N. Vo trusts overall

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

1. James Hays
2. Tsung-Yi Lin
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Karen Simonyan
7. Christian Szegedy
8. Yann LeCun
9. Nitish Srivastava
10. Andrew Zisserman

Who trusts Nam N. Vo overall

1. Liu Liu
2. Davide Cozzolino
3. Zhedong Zheng
4. Eric Müller-Budack
5. Sixing Hu
6. Yujiao Shi
7. Hongdong Li
8. Zhipeng Cai
9. Giorgos Tolias
10. Hung-Yu Tseng

Papers from Nam N. Vo's perspective

Ordered by how strongly the researchers Nam N. Vo 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. 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

• Revisiting IM2GPS in the Deep Learning Era (2017) — 182 citations
• Localizing and Orienting Street Views Using Overhead Imagery (2016) — 295 citations