Mateusz Budnik

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 433 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 57 citations into it
• Artificial Intelligence — 34 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Efficiency & Compression — 13 citations into it
• Information Retrieval & Search — 11 citations into it
• Model Architectures — 7 citations into it
• Aerospace Engineering — 6 citations into it
• Media Technology — 5 citations into it

Whom Mateusz Budnik trusts overall

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

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

Papers from Mateusz Budnik's perspective

Ordered by how strongly the researchers Mateusz Budnik 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
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

• Asymmetric metric learning for knowledge transfer (2020) — 42 citations