Justin Zhang

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 70 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it
• Model Architectures — 5 citations into it

Whom Justin Zhang trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Shaoqing Ren
4. Andrew Zisserman
5. Pedro F. Felzenszwalb
6. Alex Krizhevsky
7. Geoffrey E. Hinton

Papers from Justin Zhang's perspective

Ordered by how strongly the researchers Justin Zhang 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
4. Microsoft COCO: Common Objects in Context
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Contextual Attention for Hand Detection in the Wild (2019) — 65 citations