Xinyu Zhou

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 4 papers; trusts 503 researchers and is trusted by 1,396 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 108 citations into it; #1,118 of 21,575 by trust here, #990 by citations
• Artificial Intelligence — 70 citations into it; #9,667 of 35,345 by trust here, #4,370 by citations
• Efficiency & Compression — 42 citations into it; #30 of 1,264 by trust here, #34 by citations
• Model Architectures — 35 citations into it
• Optimization & Training — 17 citations into it
• Media Technology — 13 citations into it; #1,734 of 3,621 by trust here, #729 by citations
• ML Systems & Hardware — 12 citations into it

Whom Xinyu Zhou trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Ross B. Girshick
4. Geoffrey E. Hinton
5. Karen Simonyan
6. Andrew Zisserman
7. Yoshua Bengio
8. Ilya Sutskever
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Xinyu Zhou overall

1. Xue Yang
2. Jiahui Yu
3. Minghui Liao
4. Chunhua Shen
5. Bichen Wu
6. Christoph Feichtenhofer
7. Shangbang Long
8. Chien-Yao Wang
9. Jie Hu
10. Mingxing Tan

Papers from Xinyu Zhou's perspective

Ordered by how strongly the researchers Xinyu Zhou 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. Long Short-Term Memory
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices (2017) — 8,533 citations
• DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients (2016) — 2,283 citations
• EAST: An Efficient and Accurate Scene Text Detector (2017) — 1,675 citations
• Effective Quantization Methods for Recurrent Neural Networks (2016) — 82 citations