Yang Cong

Computer Vision and Pattern Recognition · 2011–2021

A researcher in the Science corpus: 9 papers; trusts 593 researchers and is trusted by 37 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 127 citations into it; #4,904 of 21,575 by trust here, #6,606 by citations
• Artificial Intelligence — 113 citations into it; #6,915 of 35,345 by trust here, #9,275 by citations
• Representation & Self-Supervised Learning — 28 citations into it
• Computational Mechanics — 23 citations into it
• Signal Processing — 17 citations into it; #4,628 of 7,572 by trust here, #6,083 by citations
• Safety, Robustness & Interpretability — 13 citations into it
• Meta & Continual Learning — 11 citations into it
• Aerospace Engineering — 9 citations into it

Whom Yang Cong trusts overall

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

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

Who trusts Yang Cong overall

1. Radu Tudor Ionescu
2. Mohammad Sabokrou
3. Dan Xu
4. Zhong Ji
5. Gan Sun
6. Weixin Luo
7. Wen Liu
8. Mariana-Iuliana Georgescu
9. Hyunjong Park
10. Wei-Xin Li

Papers from Yang Cong's perspective

Ordered by how strongly the researchers Yang Cong 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Sparse reconstruction cost for abnormal event detection (2011) — 843 citations
• Towards Scalable Summarization of Consumer Videos Via Sparse Dictionary Selection (2012) — 294 citations
• Abnormal event detection in crowded scenes using sparse representation (2013) — 318 citations
• Active Lifelong Learning With "Watchdog" (2018) — 35 citations
• Data Poisoning Attacks on Federated Machine Learning (2020) — 293 citations
• Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation (2021) — 153 citations
• L3DOC: Lifelong 3D Object Classification (2021) — 48 citations
• What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation (2020) — 149 citations
• I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting (2020) — 39 citations