Yongkang Wong

Computer Vision and Pattern Recognition · 2011–2022

A researcher in the Science corpus: 7 papers; trusts 549 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 160 citations into it; #15,860 of 21,575 by trust here, #9,563 by citations
• Artificial Intelligence — 128 citations into it; #30,693 of 35,345 by trust here, #15,866 by citations
• Representation & Self-Supervised Learning — 44 citations into it
• Optimization & Training — 30 citations into it
• Model Architectures — 18 citations into it
• Meta & Continual Learning — 17 citations into it
• Reinforcement Learning — 5 citations into it

Whom Yongkang Wong trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Karen Simonyan
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Andrew Zisserman
10. Ross B. Girshick

Who trusts Yongkang Wong overall

1. Conrad Sanderson
2. Görkem Algan
3. Junnan Li
4. Elad Amrani
5. Niluthpol Chowdhury Mithun
6. Hongxin Wei

Papers from Yongkang Wong's perspective

Ordered by how strongly the researchers Yongkang Wong trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Learning to Learn From Noisy Labeled Data (2018) — 372 citations
• Attention Transfer from Web Images for Video Recognition (2017) — 47 citations
• Benchmarking a Multimodal and Multiview and Interactive Dataset for Human Action Recognition (2017) — 108 citations
• A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition (2018) — 381 citations
• Learning to Predict Gradients for Semi-Supervised Continual Learning (2022) — 14 citations
• Multi-modal & Multi-view & Interactive Benchmark Dataset for Human Action Recognition (2015) — 24 citations
• Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition (2011) — 340 citations