Justin M. Johnson

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 44 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it; #18,312 of 35,345 by trust here, #17,776 by citations
• Computer Vision and Pattern Recognition — 31 citations into it

Whom Justin M. Johnson trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Alex Krizhevsky
4. Yoshua Bengio
5. Kaiming He
6. Ross B. Girshick
7. Ruslan Salakhutdinov
8. Ilya Sutskever
9. Karen Simonyan
10. Diederik P. Kingma

Who trusts Justin M. Johnson overall

1. Damien Dablain
2. Tarid Wongvorachan
3. S. Rajaraman
4. Jun Shu
5. Matloob Khushi
6. Bartosz Krawczyk
7. Surina He
8. Jenifer Siegelman
9. Tianbao Yang
10. Isar Nejadgholi

Papers from Justin M. Johnson's perspective

Ordered by how strongly the researchers Justin M. Johnson 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. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Survey on deep learning with class imbalance (2019) — 2,770 citations