Stefan Carlsson

Computer Vision and Pattern Recognition · 2001–2014

A researcher in the Science corpus: 7 papers; trusts 677 researchers and is trusted by 3,519 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 181 citations into it; #583 of 21,575 by trust here, #938 by citations
• Artificial Intelligence — 68 citations into it; #14,478 of 35,345 by trust here, #7,945 by citations
• Aerospace Engineering — 27 citations into it; #1,981 of 6,421 by trust here, #3,388 by citations
• Evaluation & Benchmarks — 25 citations into it
• Representation & Self-Supervised Learning — 20 citations into it; #1,578 of 3,145 by trust here, #1,052 by citations
• Information Retrieval & Search — 19 citations into it
• Media Technology — 17 citations into it
• Model Architectures — 9 citations into it

Whom Stefan Carlsson trusts overall

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

1. Andrew Zisserman
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yoshua Bengio
6. Ondřej Chum
7. Radford M. Neal
8. Ross B. Girshick
9. David G. Lowe
10. Kaiming He

Who trusts Stefan Carlsson overall

1. Artem Babenko
2. Yu-Xiong Wang
3. Bolei Zhou
4. Andrea Vedaldi
5. Fencheng Liu
6. Liang Zheng
7. Filip Radenovic
8. Yi Yang
9. Giorgos Tolias
10. Victor S. Lempitsky

Papers from Stefan Carlsson's perspective

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

Their papers

• CNN Features Off-the-Shelf: An Astounding Baseline for Recognition (2014) — 5,100 citations
• From generic to specific deep representations for visual recognition (2014) — 433 citations
• Factors of Transferability for a Generic ConvNet Representation (2014) — 355 citations
• 3D Pictorial Structures for Multiple View Articulated Pose Estimation (2013) — 166 citations
• Visual Instance Retrieval with Deep Convolutional Networks (2014) — 383 citations
• On the determination of residual stress and strain fields by sharp indentation testing.: Part II: experimental investigation (2001) — 170 citations
• On the determination of residual stress and strain fields by sharp indentation testing.: Part I: theoretical and numerical analysis (2001) — 270 citations