Sean Campbell

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Computer Vision and Pattern Recognition — 25 citations into it
• Model Architectures — 12 citations into it

Whom Sean Campbell trusts overall

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

1. Alex Graves
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Diederik P. Kingma
6. Yoshua Bengio
7. Sepp Hochreiter
8. J. Urgen Schmidhuber
9. Yann LeCun
10. Kaiming He

Papers from Sean Campbell's perspective

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

Their papers

• Less is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging (2020) — 37 citations
• Deep Learning vs. Traditional Computer Vision (2019) — 1,050 citations