Daniel Sedra
Computer Vision and Pattern Recognition · 2016
A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 1,233 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 17 citations into it; #1,205 of 21,575 by trust here, #1,641 by citations
- Artificial Intelligence — 16 citations into it; #1,855 of 35,345 by trust here, #2,237 by citations
- Model Architectures — 16 citations into it
- Optimization & Training — 7 citations into it; #433 of 2,601 by trust here, #204 by citations
Whom Daniel Sedra trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yoshua Bengio
- Geoffrey E. Hinton
- Kaiming He
- Ilya Sutskever
- Christian Szegedy
- Karen Simonyan
- Sergey Ioffe
- Yann LeCun
- Xavier Glorot
Who trusts Daniel Sedra overall
- Andrew Brock
- Quoc V. Le
- Gao Huang
- Christoph Feichtenhofer
- Mingxing Tan
- Zhuang Liu
- Hugo Touvron
- Barret Zoph
- Irwan Bello
- Yoshua Bengio
Papers from Daniel Sedra's perspective
Ordered by how strongly the researchers Daniel Sedra trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
- 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
Their papers
- Deep Networks with Stochastic Depth (2016) — 2,707 citations