Brian Paxton Salmon

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it; #20,729 of 21,575 by trust here, #12,172 by citations
• Media Technology — 5 citations into it; #3,447 of 3,621 by trust here, #1,423 by citations

Whom Brian Paxton Salmon trusts overall

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

1. Ilya Sutskever
2. Yushi Chen
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Yi Yang
6. Yoshua Bengio
7. Xueyun Chen
8. Liang Xiao

Who trusts Brian Paxton Salmon overall

1. Liangpei Zhang
2. Grant J. Scott
3. Yu Zhou
4. Ying Li

Papers from Brian Paxton Salmon's perspective

Ordered by how strongly the researchers Brian Paxton Salmon 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Multiview Deep Learning for Land-Use Classification (2015) — 245 citations