Hua Huang

Computer Vision and Pattern Recognition · 2014–2019

A researcher in the Science corpus: 2 papers; trusts 128 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 40 citations into it; #9,647 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 26 citations into it; #14,973 of 35,345 by trust here, #12,761 by citations
• Media Technology — 12 citations into it
• Generative Models — 10 citations into it; #904 of 1,956 by trust here, #1,010 by citations
• Meta & Continual Learning — 10 citations into it; #456 of 1,041 by trust here, #443 by citations
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Hua Huang trusts overall

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

1. Kaiming He
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Christian Szegedy
7. Andrew Zisserman
8. Yann LeCun
9. Diederik P. Kingma
10. Ian J. Goodfellow

Who trusts Hua Huang overall

1. Jiangpeng He
2. Hongjoon Ahn
3. Fei Zhu

Papers from Hua Huang's perspective

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

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

Their papers

• Incremental Learning Using Conditional Adversarial Networks (2019) — 193 citations
• No-reference image quality assessment based on spatial and spectral entropies (2014) — 705 citations