Erik Sjöblom

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it

Whom Erik Sjöblom trusts overall

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

1. Alex Krizhevsky
2. Yoshua Bengio
3. Ilya Sutskever
4. Geoffrey E. Hinton

Who trusts Erik Sjöblom overall

1. Arvid Lundervold

Papers from Erik Sjöblom's perspective

Ordered by how strongly the researchers Erik Sjöblom 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Learning Deep Architectures for AI
5. Gradient-based learning applied to document recognition
6. Deep Learning
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)

Their papers

• Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data (2017) — 99 citations
• Predicting breast tumor proliferation from whole‐slide images: The TUPAC16 challenge (2018) — 307 citations