Hong Huo

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 27 citations into it
• Artificial Intelligence — 10 citations into it
• Media Technology — 8 citations into it

Whom Hong Huo trusts overall

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

1. Tom Fawcett
2. C. Burges
3. Mark A. Hall
4. Thomas Blaschke
5. Matthew A. Turk
6. Trevor J. Hastie
7. Yi Yang
8. Marko Robnik-Sikonja
9. Zheng Zhao
10. Muhammad Aliyu Sulaiman

Papers from Hong Huo's perspective

Ordered by how strongly the researchers Hong Huo 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. ImageNet: A large-scale hierarchical image database
6. Going deeper with convolutions
7. Neural Networks for Pattern Recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Face Recognition with Convolutional Neural Networks and subspace learning (2017) — 29 citations
• Measuring the Effectiveness of Various Features for Thematic Information Extraction From Very High Resolution Remote Sensing Imagery (2015) — 28 citations