J. Alison Noble

Computer Vision and Pattern Recognition · with Gao · 2017

A researcher in the Science corpus: 1 paper; trusts 111 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 7 citations into it
• Artificial Intelligence — 6 citations into it

Whom J. Alison Noble trusts overall

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

1. Karen Simonyan
2. Andrew Zisserman
3. Damien Teney
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Andrea Vedaldi
7. Jost Tobias Springenberg
8. Kaiming He
9. Yoshua Bengio
10. Diederik P. Kingma

Papers from J. Alison Noble's perspective

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

Their papers

• Detection and Characterization of the Fetal Heartbeat in Free-hand Ultrasound Sweeps with Weakly-supervised Two-streams Convolutional Networks (2017) — 34 citations