Zhenyao Zhu

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 10 papers; trusts 600 researchers and is trusted by 159 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 157 citations into it; #2,864 of 21,575 by trust here, #3,538 by citations
• Artificial Intelligence — 151 citations into it; #16,096 of 35,345 by trust here, #8,365 by citations
• Signal Processing — 102 citations into it; #1,823 of 7,572 by trust here, #638 by citations
• Speech & Audio — 62 citations into it; #989 of 1,076 by trust here, #420 by citations
• Natural Language Processing — 55 citations into it; #5,239 of 5,688 by trust here, #573 by citations
• Model Architectures — 54 citations into it
• Representation & Self-Supervised Learning — 20 citations into it; #2,354 of 3,145 by trust here, #1,220 by citations
• Optimization & Training — 19 citations into it

Whom Zhenyao Zhu trusts overall

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

1. Geoffrey E. Hinton
2. Xiaogang Wang
3. Yi Sun
4. Alex Krizhevsky
5. Xiaoou Tang
6. Yann LeCun
7. Yoshua Bengio
8. Ilya Sutskever
9. Alex Graves
10. Kaiming He

Who trusts Zhenyao Zhu overall

1. Xiaoou Tang
2. Ping Luo
3. Yi Sun
4. Xiaogang Wang
5. Changxing Ding
6. Chaochao Lu
7. Dacheng Tao
8. Xi Yin
9. Rui Huang
10. Ayush Kumar Tewari

Papers from Zhenyao Zhu's perspective

Ordered by how strongly the researchers Zhenyao Zhu 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. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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

• Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations (2014) — 261 citations
• DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection (2014) — 165 citations
• Deep Learning Identity-Preserving Face Space (2013) — 302 citations
• Recover Canonical-View Faces in the Wild with Deep Neural Networks (2014) — 109 citations
• Face Model Compression by Distilling Knowledge from Neurons (2016) — 228 citations
• Exploring neural transducers for end-to-end speech recognition (2017) — 234 citations
• Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling (2017) — 56 citations
• Deep Speaker: an End-to-End Neural Speaker Embedding System (2017) — 533 citations
• Learning Multiscale Features Directly from Waveforms (2016) — 66 citations
• Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin (2015) — 3,177 citations