Hiroyuki Akai

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it
• Model Architectures — 6 citations into it

Whom Hiroyuki Akai trusts overall

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

1. Yoshua Bengio
2. R. Caruana
3. Geoffrey E. Hinton
4. Sergey Ioffe
5. Vinod Nair
6. Yann LeCun
7. Christian Szegedy
8. Alex Krizhevsky
9. John C. Duchi
10. Kaiming He

Who trusts Hiroyuki Akai overall

1. Rikiya Yamashita

Papers from Hiroyuki Akai's perspective

Ordered by how strongly the researchers Hiroyuki Akai 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. Gradient-based learning applied to document recognition
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Dropout: a simple way to prevent neural networks from overfitting
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study. (2017) — 595 citations
• Deep learning with convolutional neural network in radiology (2018) — 346 citations