Zehao Huang

Computer Vision and Pattern Recognition · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 934 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 133 citations into it; #4,076 of 21,575 by trust here, #7,584 by citations
• Artificial Intelligence — 97 citations into it; #4,851 of 35,345 by trust here, #10,798 by citations
• Efficiency & Compression — 48 citations into it; #175 of 1,264 by trust here, #705 by citations
• Model Architectures — 33 citations into it; #436 of 2,278 by trust here, #1,246 by citations
• Optimization & Training — 17 citations into it
• Aerospace Engineering — 8 citations into it
• Electrical and Electronic Engineering — 7 citations into it
• Neural Architecture Search & AutoML — 7 citations into it

Whom Zehao Huang trusts overall

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

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

Who trusts Zehao Huang overall

1. Charles Herrmann
2. Hesham Mostafa
3. Jindong Gu
4. Shaohui Lin
5. Xinbang Zhang
6. Angela Fan
7. Hongrong Cheng
8. Richard Strong Bowen
9. Xin Yu
10. Jiahui Yu

Papers from Zehao Huang's perspective

Ordered by how strongly the researchers Zehao Huang 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Data-Driven Sparse Structure Selection for Deep Neural Networks (2017) — 617 citations
• You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization (2018) — 100 citations
• QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection (2021) — 450 citations