Yoshihiro Yamada

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 102 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 27 citations into it; #9,686 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 26 citations into it; #15,013 of 35,345 by trust here, #15,236 by citations
• Optimization & Training — 17 citations into it; #962 of 2,601 by trust here, #1,083 by citations
• Model Architectures — 12 citations into it; #930 of 2,278 by trust here, #1,572 by citations

Whom Yoshihiro Yamada trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Xavier Gastaldi
6. Sergey Ioffe
7. Ilya Sutskever
8. X. Zhang
9. Ross B. Girshick
10. Yoshua Bengio

Who trusts Yoshihiro Yamada overall

1. Ekin Dogus Cubuk
2. Yu Cheng
3. Barret Zoph
4. Quoc V. Le
5. Tommaso Furlanello
6. Boyi Li
7. Ethan Harris
8. Arild Nøkland
9. Golnaz Ghiasi
10. Qizhe Xie

Papers from Yoshihiro Yamada's perspective

Ordered by how strongly the researchers Yoshihiro Yamada 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. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Shakedrop Regularization for Deep Residual Learning (2018) — 179 citations
• Deep Pyramidal Residual Networks with Separated Stochastic Depth (2016) — 28 citations
• ShakeDrop regularization (2018) — 71 citations