Xinyu Li
Control and Systems Engineering · IEEE transactions on industrial electronics (1982. Print) · 2016–2019
A researcher in the Science corpus: 4 papers; trusts 83 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Control and Systems Engineering — 42 citations into it; #1,566 of 8,257 by trust here, #1,372 by citations
- Artificial Intelligence — 28 citations into it
- Mechanical Engineering — 18 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Industrial and Manufacturing Engineering — 14 citations into it; #933 of 2,521 by trust here, #896 by citations
- Mechanics of Materials — 13 citations into it; #1,821 of 6,291 by trust here, #2,631 by citations
- Representation & Self-Supervised Learning — 11 citations into it
- Signal Processing — 6 citations into it
Whom Xinyu Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Hilton Wolpert
- Fred W. Glover
- J. Tay
- Imran Ali Chaudhry
- Yoshua Bengio
- Alex Krizhevsky
- Geoffrey E. Hinton
- Imed Kacem
- Parviz Fattahi
- Kaiming He
Who trusts Xinyu Li overall
- Long Wen
- Shen Zhang
- Rui Yang
- Dhiraj Neupane
- Te Han
- Boyuan Yang
- Mohamed Loey
- Liang Gao
- Shibo Zhang
- Huan Wang
Papers from Xinyu Li's perspective
Ordered by how strongly the researchers Xinyu Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis (2019) — 927 citations
- A transfer convolutional neural network for fault diagnosis based on ResNet-50 (2019) — 677 citations
- A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method (2018) — 1,795 citations
- An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem (2016) — 535 citations