Alexander V. Buslaev

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 4 papers; trusts 277 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it; #9,803 of 21,575 by trust here, #8,021 by citations
• Artificial Intelligence — 51 citations into it
• Media Technology — 20 citations into it; #2,505 of 3,621 by trust here, #2,114 by citations
• Model Architectures — 13 citations into it
• Optimization & Training — 12 citations into it
• Biophysics — 10 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Biomedical Engineering — 8 citations into it

Whom Alexander V. Buslaev trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Vladimir I. Iglovikov
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Ross B. Girshick
8. Yann LeCun
9. Evan Shelhamer
10. Olaf Ronneberger

Who trusts Alexander V. Buslaev overall

1. Sergey I. Nikolenko
2. Alexander Rakhlin
3. Artur Kuzin
4. S. Hasan
5. Kaede Shiohara
6. Zoe Papakipos
7. Vladimir I. Iglovikov
8. Yauhen Babakhin
9. Fernando Pérez-García
10. Yunjie Tian

Papers from Alexander V. Buslaev's perspective

Ordered by how strongly the researchers Alexander V. Buslaev 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Albumentations: fast and flexible image augmentations (2018) — 2,644 citations
• Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery (2018) — 164 citations
• Feature Pyramid Network for Multi-class Land Segmentation (2018) — 165 citations
• TernausNetV2: Fully Convolutional Network for Instance Segmentation (2018) — 160 citations