Weihua Li

Control and Systems Engineering · Energy · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 15 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 46 citations into it; #1,871 of 8,257 by trust here, #2,078 by citations
• Mechanical Engineering — 27 citations into it
• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it

Whom Weihua Li trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. L. V. D. van der Maaten
4. Prasanna Tamilselvan
5. Yann LeCun
6. Alex Krizhevsky
7. Abdenour Soualhi
8. Haidong Shao
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Weihua Li overall

1. Shen Zhang
2. Meng Ma
3. Weiting Zhang
4. Shibo Zhang
5. Wu Deng
6. Zhu Mao
7. Carlos Vidal
8. Bingnan Wang

Papers from Weihua Li's perspective

Ordered by how strongly the researchers Weihua Li 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network (2019) — 461 citations
• State-of-charge estimation of lithium-ion batteries using LSTM and UKF (2020) — 398 citations
• A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks (2020) — 420 citations
• Bearing performance degradation assessment using long short-term memory recurrent network (2019) — 316 citations
• Mechanical fault diagnosis using Convolutional Neural Networks and Extreme Learning Machine (2019) — 321 citations
• Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network (2017) — 754 citations