Mikhail Belyaev

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 42 citations into it
• Model Architectures — 12 citations into it
• Biophysics — 5 citations into it
• Media Technology — 5 citations into it

Whom Mikhail Belyaev trusts overall

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

1. Brian B. Avants
2. Karen Simonyan
3. Konstantinos Kamnitsas
4. Olaf Ronneberger
5. Kaiming He

Papers from Mikhail Belyaev's perspective

Ordered by how strongly the researchers Mikhail Belyaev 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. ImageNet classification with deep convolutional neural networks
6. Dropout: a simple way to prevent neural networks from overfitting
7. Densely Connected Convolutional Networks
8. Gradient-based learning applied to document recognition
9. Visualizing and Understanding Convolutional Networks
10. Identity Mappings in Deep Residual Networks

Their papers

• Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge (2019) — 315 citations
• Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection (2019) — 26 citations
• MRI Augmentation via Elastic Registration for Brain Lesions Segmentation (2017) — 13 citations
• Residual and plain convolutional neural networks for 3D brain MRI classification (2017) — 446 citations