Xinghua Lou

Computer Vision and Pattern Recognition · 2017

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

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it

Whom Xinghua Lou trusts

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

1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
2. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Xinghua Lou's perspective

Ordered by how strongly the researchers Xinghua Lou trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. ImageNet: A large-scale hierarchical image database
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Asynchronous Methods for Deep Reinforcement Learning
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. DRAW: A Recurrent Neural Network For Image Generation
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics (2017) — 246 citations
• A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs (2017) — 270 citations