Bertram E. Shi

Computer Vision and Pattern Recognition · 2015–2017

A researcher in the Science corpus: 4 papers; trusts 354 researchers and is trusted by 97 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 88 citations into it; #3,308 of 21,575 by trust here, #6,737 by citations
• Artificial Intelligence — 52 citations into it; #12,160 of 35,345 by trust here, #9,557 by citations
• Representation & Self-Supervised Learning — 19 citations into it
• Model Architectures — 13 citations into it
• Electrical and Electronic Engineering — 11 citations into it; #15,682 of 16,539 by trust here, #11,641 by citations
• Optimization & Training — 10 citations into it
• Cellular and Molecular Neuroscience — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it

Whom Bertram E. Shi trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Yann LeCun
5. Karen Simonyan
6. David G. Lowe
7. Ilya Sutskever
8. L. Eon Bottou
9. Kaiming He
10. Andrew Zisserman

Who trusts Bertram E. Shi overall

1. Christoph Feichtenhofer
2. Ali Diba
3. Limin Wang

Papers from Bertram E. Shi's perspective

Ordered by how strongly the researchers Bertram E. Shi 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. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks (2015) — 551 citations
• Lattice Long Short-Term Memory for Human Action Recognition (2017) — 174 citations
• HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition (2017) — 656 citations
• Laplacian Auto-Encoders: An explicit learning of nonlinear data manifold (2015) — 76 citations