Jeffrey N. Chiang

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 57 citations into it
• Artificial Intelligence — 42 citations into it

Whom Jeffrey N. Chiang trusts overall

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

1. Yarin Gal
2. Geoffrey E. Hinton

Papers from Jeffrey N. Chiang's perspective

Ordered by how strongly the researchers Jeffrey N. Chiang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation (2019) — 1,007 citations