Hiroshi Omata

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 109 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it
• Artificial Intelligence — 10 citations into it

Whom Hiroshi Omata trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Christian Szegedy
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Shaoqing Ren
7. Joseph Redmon
8. Pedro F. Felzenszwalb
9. Yann LeCun
10. Jia Deng

Papers from Hiroshi Omata's perspective

Ordered by how strongly the researchers Hiroshi Omata 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. ImageNet: A large-scale hierarchical image database
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
6. Gradient-based learning applied to document recognition
7. Microsoft COCO: Common Objects in Context
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images (2018) — 827 citations