Grant Haskins

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 179 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 71 citations into it
• Artificial Intelligence — 38 citations into it
• Radiology, Nuclear Medicine and Imaging — 28 citations into it
• Biomedical Engineering — 15 citations into it
• Model Architectures — 15 citations into it
• Generative Models — 10 citations into it
• Reinforcement Learning — 10 citations into it
• Aerospace Engineering — 6 citations into it

Whom Grant Haskins trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Christian Szegedy
4. Kaiming He
5. J. Urgen Schmidhuber
6. Karen Simonyan
7. Yoshua Bengio
8. Sergey Ioffe
9. Yann LeCun
10. Sepp Hochreiter

Who trusts Grant Haskins overall

1. Xuxin Chen
2. Xingyu Jiang
3. Jiayi Ma

Papers from Grant Haskins's perspective

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

Their papers

• Deep learning in medical image registration: a survey (2019) — 682 citations
• Learning deep similarity metric for 3D MR–TRUS image registration (2018) — 124 citations