Laurence Tianruo Yang

Artificial Intelligence · 2012–2021

A researcher in the Science corpus: 13 papers; trusts 97 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 167 citations into it; #13,353 of 35,345 by trust here, #8,999 by citations
• Computer Vision and Pattern Recognition — 131 citations into it
• Electrical and Electronic Engineering — 62 citations into it
• Signal Processing — 41 citations into it
• Biomedical Engineering — 33 citations into it
• Control and Systems Engineering — 31 citations into it
• Information Systems — 30 citations into it
• Model Architectures — 28 citations into it

Whom Laurence Tianruo Yang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Pascal Vincent
4. Alex Krizhevsky
5. Yann LeCun
6. Ruslan Salakhutdinov
7. Diederik P. Kingma
8. Kaiming He
9. Ilya Sutskever
10. Craig Gentry

Who trusts Laurence Tianruo Yang overall

1. Evgin Göçeri
2. Ahmed El Ouadrhiri
3. Ehsan Hesamifard
4. Qinbin Li
5. Ping Li
6. Billy Pik Lik Lau
7. Wenxiu Ding
8. Bomin Mao

Papers from Laurence Tianruo Yang's perspective

Ordered by how strongly the researchers Laurence Tianruo 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. Gradient-based learning applied to document recognition
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A kernel machine-based secure data sensing and fusion scheme in wireless sensor networks for the cyber-physical systems (2016) — 103 citations
• Context-aware vehicular cyber-physical systems with cloud support: architecture, challenges, and solutions (2014) — 364 citations
• Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in the Smart Grid (2012) — 113 citations
• Deep-Learning-Enhanced Human Activity Recognition for Internet of Healthcare Things (2020) — 406 citations
• Role-Dependent Privacy Preservation for Secure V2G Networks in the Smart Grid (2014) — 116 citations
• Convolutional neural networks for medical image analysis: State-of-the-art, comparisons, improvement and perspectives (2021) — 369 citations
• A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019) — 203 citations
• Data fusion in cyber-physical-social systems: State-of-the-art and perspectives (2019) — 110 citations
• Big data fusion in Internet of Things (2018) — 17 citations
• A survey on deep learning for big data (2018) — 726 citations
• Deep Computation Model for Unsupervised Feature Learning on Big Data (2016) — 138 citations
• Privacy Preserving Deep Computation Model on Cloud for Big Data Feature Learning (2016) — 261 citations
• Data Mining for Internet of Things: A Survey (2014) — 613 citations