Du Q. Huynh

Computer Vision and Pattern Recognition · 2009–2019

A researcher in the Science corpus: 7 papers; trusts 904 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 169 citations into it; #3,743 of 21,575 by trust here, #5,161 by citations
• Artificial Intelligence — 65 citations into it; #12,931 of 35,345 by trust here, #17,412 by citations
• Biomedical Engineering — 46 citations into it; #1,285 of 10,734 by trust here, #4,314 by citations
• Human-Computer Interaction — 35 citations into it; #1,233 of 2,253 by trust here, #1,081 by citations
• 3D Vision & Pose — 27 citations into it; #409 of 689 by trust here, #513 by citations
• Endocrinology, Diabetes and Metabolism — 10 citations into it
• Aerospace Engineering — 9 citations into it; #598 of 6,421 by trust here, #3,388 by citations
• Model Architectures — 9 citations into it

Whom Du Q. Huynh trusts overall

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

1. James J. Kuffner Jr.
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Andrew Zisserman
6. Yoshua Bengio
7. Karen Simonyan
8. Ross B. Girshick
9. David G. Lowe
10. Ilya Sutskever

Who trusts Du Q. Huynh overall

1. Hossein Rahmani
2. Mohammed Bennamoun
3. Seyed Sadegh Mohseni Salehi
4. Sergio Garrido-Jurado
5. Samarth Brahmbhatt
6. Ajmal Saeed Mian
7. Rishi Rajalingham
8. Jun Liu
9. Amir Shahroudy
10. Zehua Sun

Papers from Du Q. Huynh's perspective

Ordered by how strongly the researchers Du Q. Huynh 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. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Metrics for 3D Rotations: Comparison and Analysis (2009) — 752 citations
• SS-LSTM: A Hierarchical LSTM Model for Pedestrian Trajectory Prediction (2018) — 411 citations
• Histogram of Oriented Principal Components for Cross-View Action Recognition (2014) — 194 citations
• HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition (2014) — 194 citations
• Real time action recognition using histograms of depth gradients and random decision forests (2014) — 116 citations
• Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition With CNNs (2019) — 101 citations
• Action Classification with Locality-Constrained Linear Coding (2014) — 25 citations