Justin S. Paul

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 5 citations into it; #15,229 of 21,575 by trust here, #16,367 by citations

Whom Justin S. Paul trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Ilya Sutskever
4. Nitish Srivastava
5. Yoshua Bengio
6. Yann LeCun
7. Simon Osindero
8. Ruslan Salakhutdinov
9. Radford M. Neal
10. Yee Whye Teh

Who trusts Justin S. Paul overall

1. Parnian Afshar
2. Hossam H. Sultan
3. Jaeyong Kang
4. Soheila Saeedi
5. K. Plataniotis
6. Arash Mohammadi
7. Nancy M. Salem
8. Zahid Ullah
9. Sorayya Rezayi

Papers from Justin S. Paul's perspective

Ordered by how strongly the researchers Justin S. Paul trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Dropout: a simple way to prevent neural networks from overfitting
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep Learning for Brain Tumor Classification (2017) — 329 citations