Tristan Anselm Kuder

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 — 21 citations into it
• Artificial Intelligence — 9 citations into it

Whom Tristan Anselm Kuder trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Diederik P. Kingma
4. Tsung-Yi Lin
5. Geoffrey E. Hinton
6. Alex Krizhevsky

Papers from Tristan Anselm Kuder's perspective

Ordered by how strongly the researchers Tristan Anselm Kuder 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Going deeper with convolutions
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection (2018) — 233 citations