Thomas Stark

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Media Technology — 11 citations into it

Whom Thomas Stark trusts overall

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

1. Karen Simonyan
2. Andrew Zisserman
3. Sinno Jialin Pan
4. Evan Shelhamer
5. Alex Krizhevsky
6. Geoffrey E. Hinton
7. Fan Hu
8. Emmanuel Maggiori

Papers from Thomas Stark's perspective

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

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

Their papers

• Semantic segmentation of slums in satellite images using transfer learning on fully convolutional neural networks (2019) — 321 citations