Jianghao Shen

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it
• Artificial Intelligence — 45 citations into it
• Efficiency & Compression — 40 citations into it

Whom Jianghao Shen trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Song Han
5. Ross B. Girshick
6. Ilya Sutskever
7. Yoshua Bengio
8. Yann LeCun
9. Diederik P. Kingma
10. Karen Simonyan

Papers from Jianghao Shen's perspective

Ordered by how strongly the researchers Jianghao Shen 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference (2019) — 93 citations
• Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference (2020) — 49 citations