Jing Yang

Computer Vision and Pattern Recognition · with Li · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 515 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 208 citations into it
• Artificial Intelligence — 146 citations into it
• Model Architectures — 71 citations into it
• Optimization & Training — 34 citations into it
• Efficiency & Compression — 33 citations into it

Whom Jing Yang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Yann LeCun
7. Shaoqing Ren
8. Ilya Sutskever
9. Diederik P. Kingma
10. Christian Szegedy

Papers from Jing Yang's perspective

Ordered by how strongly the researchers Jing Yang 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. 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. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Review of Image Classification Algorithms Based on Convolutional Neural Networks (2021) — 697 citations
• Using Deep Learning to Detect Defects in Manufacturing: A Comprehensive Survey and Current Challenges (2020) — 415 citations