Mo Zhou

Computer Vision and Pattern Recognition · with Hua · 2016–2021

A researcher in the Science corpus: 2 papers; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it
• Artificial Intelligence — 27 citations into it
• Automotive Engineering — 9 citations into it

Whom Mo Zhou trusts overall

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

1. Yun Fu
2. Paul A. Viola
3. Diederik P. Kingma
4. Kaiming He
5. Koby Crammer
6. Geoffrey E. Hinton
7. Eibe Frank
8. Karl Ricanek Jr.
9. Ling Li
10. Alex Krizhevsky

Who trusts Mo Zhou overall

1. Hee Jung Ryu
2. Di Kang
3. Wenzhi Cao

Papers from Mo Zhou's perspective

Ordered by how strongly the researchers Mo Zhou 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. GENERATIVE ADVERSARIAL NETS
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Ordinal Regression with Multiple Output CNN for Age Estimation (2016) — 696 citations
• SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction (2021) — 365 citations