Emil Brissman

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 104 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it; #20,181 of 21,575 by trust here, #16,367 by citations

Whom Emil Brissman trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Federico Perazzi
5. Karen Simonyan
6. Ross B. Girshick
7. Jordi Pont-Tuset
8. Andrew Zisserman
9. Ilya Sutskever
10. Yann LeCun

Who trusts Emil Brissman overall

1. Ho Kei Cheng

Papers from Emil Brissman's perspective

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

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

Their papers

• A Generative Appearance Model for End-To-End Video Object Segmentation (2018) — 199 citations