Dan Levi
Computer Vision and Pattern Recognition · 2012–2017
A researcher in the Science corpus: 3 papers; trusts 217 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 40 citations into it; #9,203 of 21,575 by trust here, #14,478 by citations
- Artificial Intelligence — 18 citations into it
- Automotive Engineering — 12 citations into it; #1,823 of 3,081 by trust here, #1,636 by citations
- Optimization & Training — 7 citations into it
- Efficiency & Compression — 6 citations into it
- Environmental Engineering — 6 citations into it
Whom Dan Levi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ronald J. Williams
- Yoshua Bengio
- Kaiming He
- Sergey Ioffe
- Max Welling
- Yann LeCun
- Ilya Sutskever
Who trusts Dan Levi overall
- Martin Danelljan
- Gustav Häger
- Fahad Shahbaz Khan
- Simon Wiedemann
- Minsik Cho
- Pierre Stock
- Michael Felsberg
- Mart van Baalen
- Yang Li
- Alberto Yukinobu Hata
Papers from Dan Levi's perspective
Ordered by how strongly the researchers Dan Levi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Locally Orderless Tracking (2012) — 490 citations
- Learning Discrete Weights Using the Local Reparameterization Trick (2017) — 92 citations
- Recent progress in road and lane detection: a survey (2014) — 788 citations