Peter Naylor

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 36 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 22 citations into it; #19,380 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 17 citations into it; #31,552 of 35,345 by trust here, #25,809 by citations
• Biophysics — 12 citations into it

Whom Peter Naylor trusts overall

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

1. Kaiming He
2. Fuyong Xing
3. Xavier Glorot
4. Yoshua Bengio
5. Alex Krizhevsky
6. Evan Shelhamer
7. Geoffrey E. Hinton
8. Ross B. Girshick
9. Andrew Janowczyk
10. Dan Claudiu Ciresan

Who trusts Peter Naylor overall

1. Simon Graham
2. Massimo Salvi
3. Faisal Mahmood
4. Fabian Hörst
5. David B. A. Epstein
6. Nasir M. Rajpoot
7. Richard J. Chen
8. Usha R. Acharya

Papers from Peter Naylor's perspective

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

Their papers

• Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map (2019) — 666 citations