Noriaki Hirose

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 4 papers; trusts 274 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 86 citations into it; #18,248 of 21,575 by trust here, #8,831 by citations
• Artificial Intelligence — 55 citations into it
• Reinforcement Learning — 24 citations into it
• Aerospace Engineering — 20 citations into it; #5,839 of 6,421 by trust here, #4,205 by citations
• Robotics & Control — 20 citations into it
• Control and Systems Engineering — 17 citations into it
• Generative Models — 15 citations into it
• Model Architectures — 8 citations into it

Whom Noriaki Hirose trusts overall

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

1. Yoshua Bengio
2. Kaiming He
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Sebastian Thrun
7. Diederik P. Kingma
8. Yann LeCun
9. Individualized Treat
10. Andrew Zisserman

Who trusts Noriaki Hirose overall

1. Dhruv Shah
2. Gregory Kahn
3. Fei Xia
4. Sergey Levine
5. Lorenz Wellhausen
6. Pieter Abbeel
7. Ajay Kumar Sridhar
8. Roberto Mart'in-Mart'in
9. Blazej Osinski

Papers from Noriaki Hirose's perspective

Ordered by how strongly the researchers Noriaki Hirose 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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

• SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints (2018) — 1,077 citations
• GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation (2018) — 89 citations
• Deep Visual MPC-Policy Learning for Navigation (2019) — 123 citations
• ViNT: A Foundation Model for Visual Navigation (2023) — 346 citations