Sheng-Jun Huang

Artificial Intelligence · 2008–2018

A researcher in the Science corpus: 3 papers; trusts 226 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 109 citations into it; #12,785 of 35,345 by trust here, #11,921 by citations
• Computer Vision and Pattern Recognition — 69 citations into it; #14,455 of 21,575 by trust here, #10,010 by citations
• Representation & Self-Supervised Learning — 18 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Information Systems — 13 citations into it
• Statistical Learning Theory — 13 citations into it
• Radiology, Nuclear Medicine and Imaging — 11 citations into it
• Computational Mechanics — 8 citations into it

Whom Sheng-Jun Huang trusts overall

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

1. Geoffrey E. Hinton
2. Fabrizio Sebastiani
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Min-Ling Zhang
7. Andre´ Elisseeff
8. Diederik P. Kingma
9. Kaiming He
10. Walter J. Scheirer

Who trusts Sheng-Jun Huang overall

1. Da-Wei Zhou
2. Han-Jia Ye
3. Zhi-Hua Zhou
4. Yassine Ouali
5. Thomas Drugman
6. J. Ash
7. Yang Yang
8. De-chuan Zhan
9. Mohamad Mahmoud Al Rahhal
10. Céline Hudelot

Papers from Sheng-Jun Huang's perspective

Ordered by how strongly the researchers Sheng-Jun 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet Large Scale Visual Recognition Challenge
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Recent Advances in Open Set Recognition: A Survey (2018) — 1,029 citations
• Active Learning by Querying Informative and Representative Examples (2010) — 731 citations
• Multi-instance multi-label learning (2008) — 431 citations