Yuequan Bao
Civil and Structural Engineering · 2011–2020
A researcher in the Science corpus: 5 papers; trusts 50 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Civil and Structural Engineering — 24 citations into it; #1,354 of 6,160 by trust here, #2,587 by citations
- Computer Vision and Pattern Recognition — 23 citations into it
- Artificial Intelligence — 20 citations into it; #17,319 of 35,345 by trust here, #23,077 by citations
- Computational Mechanics — 10 citations into it
Whom Yuequan Bao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zhiyi Tang
- Yoshua Bengio
- Johannes L. Schönberger
- Yuqing Gao
- Billie F. Spencer Jr.
- Jia Deng
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yann LeCun
- Zhicheng Chen
Who trusts Yuequan Bao overall
- Mohsen Azimi
- Hui Li
- Zhiyi Tang
- Sattar Dorafshan
- Kukjin Choi
- Mikel Canizo
- Sandeep Sony
- Armin Dadras Eslamlou
- Zhicheng Chen
- Gokhan Pekcan
Papers from Yuequan Bao's perspective
Ordered by how strongly the researchers Yuequan Bao 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Machine learning paradigm for structural health monitoring (2020) — 306 citations
- Computer vision and deep learning–based data anomaly detection method for structural health monitoring (2019) — 529 citations
- The State of the Art of Data Science and Engineering in Structural Health Monitoring (2019) — 436 citations
- Convolutional neural network‐based data anomaly detection method using multiple information for structural health monitoring (2018) — 384 citations
- Compressive sampling for accelerometer signals in structural health monitoring (2011) — 169 citations