Kim-Hui Yap

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 241 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it; #16,054 of 21,575 by trust here, #9,872 by citations
• Generative Models — 18 citations into it; #1,505 of 1,956 by trust here, #1,221 by citations
• Artificial Intelligence — 16 citations into it
• Biomedical Engineering — 6 citations into it

Whom Kim-Hui Yap trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Yann LeCun
4. Alex Krizhevsky
5. Yoshua Bengio
6. Diederik P. Kingma
7. Ross B. Girshick
8. Jia Deng
9. Ian J. Goodfellow
10. Ilya Sutskever

Who trusts Kim-Hui Yap overall

1. Animesh Karnewar

Papers from Kim-Hui Yap's perspective

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

Their papers

• The Unusual Effectiveness of Averaging in GAN Training (2018) — 183 citations
• AANet: Attribute Attention Network for Person Re-Identifications (2019) — 332 citations