Li Cheng
Civil and Structural Engineering · with Jing · 2001–2017
A researcher in the Science corpus: 13 papers; trusts 86 researchers and is trusted by 13 researchers here, as inferred from the citation graph.
Subfields
- Civil and Structural Engineering — 45 citations into it; #2,803 of 6,160 by trust here, #2,464 by citations
- Mechanics of Materials — 29 citations into it
- Computer Vision and Pattern Recognition — 27 citations into it; #11,135 of 21,575 by trust here, #9,563 by citations
- Biomedical Engineering — 26 citations into it; #4,027 of 10,734 by trust here, #6,028 by citations
- Mechanical Engineering — 23 citations into it; #5,812 of 8,300 by trust here, #5,361 by citations
- Artificial Intelligence — 17 citations into it; #33,259 of 35,345 by trust here, #19,873 by citations
- Control and Systems Engineering — 15 citations into it; #6,230 of 8,257 by trust here, #4,514 by citations
- Aerospace Engineering — 6 citations into it
Whom Li Cheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David A. McAllester
- David G. Lowe
- V. Krylov
- Serge J. Belongie
- Matthijs C. Dorst
- Quoc Hung Nguyen
- Andrew Zisserman
- Geoffrey E. Hinton
- Josef Sivic
- Yoshua Bengio
Who trusts Li Cheng overall
- Wei-Ming Leea
- Quanshi Zhang
- Hema Swetha Koppula
- Yu Kong
- Jeng-Tzong Chenb
- Xiuting Sun
- A. Pelat
- Lorenzo Torresani
- Julian McAuley
- Bingbing Ni
Papers from Li Cheng's perspective
Ordered by how strongly the researchers Li Cheng 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models (2011) — 148 citations
- Learning Graph Matching (2007) — 465 citations
- American and Chinese parental involvement in young children's mathematics learning (2006) — 110 citations
- Characterization of acoustic black hole effect using a one-dimensional fully-coupled and wavelet-decomposed semi-analytical model (2016) — 225 citations
- Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-Free and More Effective (2017) — 114 citations
- Effect of limited matrix–reinforcement interfacial reaction on enhancing the mechanical properties of aluminium–silicon carbide composites (2001) — 283 citations
- Broadband locally resonant band gaps in periodic beam structures with embedded acoustic black holes (2017) — 149 citations
- Multi-damage localization on large complex structures through an extended delay-and-sum based method (2016) — 67 citations
- Vibration isolation via a scissor-like structured platform (2014) — 245 citations
- Beneficial performance of a quasi-zero-stiffness vibration isolator with time-delayed active control (2014) — 169 citations
- Acousto-ultrasonics-based fatigue damage characterization: Linear versus nonlinear signal features (2014) — 184 citations
- Magnetorheological fluid dampers: A review on structure design and analysis (2012) — 353 citations
- Vibration analysis of annular-like plates (2003) — 53 citations