Kristin J. Dana

Computer Vision and Pattern Recognition · 1999–2018

A researcher in the Science corpus: 4 papers; trusts 645 researchers and is trusted by 734 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 105 citations into it; #1,608 of 21,575 by trust here, #3,017 by citations
• Artificial Intelligence — 38 citations into it
• Generative Models — 18 citations into it; #765 of 1,956 by trust here, #1,355 by citations
• Model Architectures — 16 citations into it
• Computer Graphics and Computer-Aided Design — 15 citations into it
• Optimization & Training — 10 citations into it
• Aerospace Engineering — 8 citations into it
• ML Systems & Hardware — 5 citations into it

Whom Kristin J. Dana trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. David G. Lowe
4. Geoffrey E. Hinton
5. Karen Simonyan
6. Ross B. Girshick
7. Andrew Zisserman
8. Yoshua Bengio
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Kristin J. Dana overall

1. Manik Varma
2. Andrew Zisserman
3. Mircea Cimpoi
4. Barbara Caputo
5. Sean Bell
6. Jitendra Malik
7. Christopher Kanan
8. Svetlana Lazebnik
9. Eric Hayman
10. Zizhao Zhang

Papers from Kristin J. Dana's perspective

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

Their papers

• Context Encoding for Semantic Segmentation (2018) — 1,368 citations
• Reflectance and texture of real-world surfaces (1999)
• Multi-style Generative Network for Real-time Transfer (2017) — 306 citations
• Automated Crack Detection on Concrete Bridges (2016) — 405 citations