John Cohn

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 40 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 39 citations into it
• Artificial Intelligence — 29 citations into it
• Efficiency & Compression — 25 citations into it

Whom John Cohn trusts overall

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

1. Alex Krizhevsky
2. Song Han
3. Kaiming He
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Pete Warden
7. Jia Deng
8. Yihui He
9. Yann LeCun
10. Diederik P. Kingma

Papers from John Cohn's perspective

Ordered by how strongly the researchers John Cohn trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• MCUNet: Tiny Deep Learning on IoT Devices (2020) — 741 citations