Minghang Zhao

Control and Systems Engineering · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 20 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Artificial Intelligence — 13 citations into it
• Mechanical Engineering — 12 citations into it
• Model Architectures — 10 citations into it
• Optimization & Training — 6 citations into it

Whom Minghang Zhao trusts overall

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

1. Kaiming He
2. X. Zhang
3. Sergey Ioffe
4. Shaoqing Ren
5. Christian Szegedy
6. David L. Donoho
7. Geoffrey E. Hinton
8. Yann LeCun
9. Yoshua Bengio
10. Alex Krizhevsky

Who trusts Minghang Zhao overall

1. Jinyang Jiao
2. Shen Zhang
3. Ming Zhao

Papers from Minghang Zhao's perspective

Ordered by how strongly the researchers Minghang Zhao 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep Residual Shrinkage Networks for Fault Diagnosis (2020) — 1,184 citations
• Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes (2018) — 331 citations
• Bearing remaining useful life estimation based on time–frequency representation and supervised dimensionality reduction (2016) — 104 citations