David K. Han

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 4 papers; trusts 136 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 32 citations into it; #12,297 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 15 citations into it
• Generative Models — 15 citations into it; #1,198 of 1,956 by trust here, #1,843 by citations
• Human-Computer Interaction — 5 citations into it
• Optimization & Training — 5 citations into it

Whom David K. Han trusts overall

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

1. Diederik P. Kingma
2. Lawrence R. Rabiner
3. Kaiming He
4. Geoffrey E. Hinton
5. G. Johansson
6. Inderjit S. Dhillon
7. Alex Krizhevsky
8. Yoshua Bengio
9. Ross B. Girshick
10. Yann LeCun

Who trusts David K. Han overall

1. Ekin Dogus Cubuk
2. Barret Zoph
3. Xiao Wang

Papers from David K. Han's perspective

Ordered by how strongly the researchers David K. Han 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Generative Adversarial Network Based Acoustic Scene Training Set Augmentation and Selection Using SVM Hyper-Plane (2017) — 139 citations
• Learning Object Placement by Inpainting for Compositional Data Augmentation (2020) — 79 citations
• Generative Adversarial Network Based Acoustic Scene Training Set Augmentation and Selection Using SVM Hyper-Plane (2017)
• Hidden Markov Model on a unit hypersphere space for gesture trajectory recognition (2014) — 35 citations