Ryo Takahashi

Computer Vision and Pattern Recognition · with Matsubara · 2018

A researcher in the Science corpus: 2 papers; trusts 491 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it; #11,341 of 21,575 by trust here, #14,151 by citations
• Artificial Intelligence — 50 citations into it; #28,706 of 35,345 by trust here, #27,551 by citations
• Model Architectures — 24 citations into it
• Optimization & Training — 18 citations into it
• Safety, Robustness & Interpretability — 8 citations into it

Whom Ryo Takahashi trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Diederik P. Kingma
6. Sergey Ioffe
7. Yann LeCun
8. Christian Szegedy
9. Yoshua Bengio
10. X. Zhang

Who trusts Ryo Takahashi overall

1. Sylvestre-Alvise Rebuffi
2. Maithra Raghu
3. Yoshihiro Yamada
4. Sven Gowal
5. Erica Schmidt
6. Dan A. Calian
7. Masakazu Iwamura
8. Florian Stimberg
9. Cherry Khosla

Papers from Ryo Takahashi's perspective

Ordered by how strongly the researchers Ryo Takahashi 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Data Augmentation Using Random Image Cropping and Patching for Deep CNNs (2018) — 406 citations
• RICAP: Random Image Cropping and Patching Data Augmentation for Deep CNNs (2018) — 131 citations