Joshua T. Abbott

Computer Vision and Pattern Recognition · 2016

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 — 8 citations into it
• Artificial Intelligence — 7 citations into it

Whom Joshua T. Abbott trusts overall

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

1. Karen Simonyan
2. Christian Szegedy
3. Yoshua Bengio
4. Yangqing Jia
5. Andrew Zisserman
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Yann LeCun
9. Kaiming He
10. Ilya Sutskever

Who trusts Joshua T. Abbott overall

1. Drew Linsley

Papers from Joshua T. Abbott's perspective

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

Their papers

• Adapting Deep Network Features to Capture Psychological Representations (2016) — 72 citations