Naoyuki Kubota

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 17 citations into it
• Artificial Intelligence — 10 citations into it
• Model Architectures — 6 citations into it
• Reinforcement Learning — 6 citations into it

Whom Naoyuki Kubota trusts overall

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

1. Richard S. Sutton
2. Michael L. Littman
3. Christopher J. C. H. Watkins
4. Kaiming He
5. Karen Simonyan
6. Andrew Barto
7. Christian Szegedy
8. Geoffrey E. Hinton

Papers from Naoyuki Kubota's perspective

Ordered by how strongly the researchers Naoyuki Kubota 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. Gradient-based learning applied to document recognition
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Reinforcement Learning: An Introduction
9. ImageNet Large Scale Visual Recognition Challenge
10. Densely Connected Convolutional Networks

Their papers

• Reinforcement Learning in non-stationary environments: An intrinsically motivated stress based memory retrieval performance (SBMRP) model (2014) — 10 citations
• Attention mechanism-based CNN for facial expression recognition (2020) — 312 citations