David Feinzimer

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 57 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 18 citations into it
• Artificial Intelligence — 12 citations into it
• Model Architectures — 10 citations into it
• Optimization & Training — 5 citations into it

Whom David Feinzimer trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Christian Szegedy
4. Alex Krizhevsky
5. Yann LeCun
6. Yoshua Bengio
7. Karen Simonyan
8. Jia Deng
9. Yangqing Jia
10. Ross B. Girshick

Papers from David Feinzimer's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Long Short-Term Memory
5. ImageNet Large Scale Visual Recognition Challenge
6. Going deeper with convolutions
7. Gradient-based learning applied to document recognition
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Compressed residual-VGG16 CNN model for big data places image recognition (2018) — 395 citations