Naofumi Tomita

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 16 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 — 13 citations into it

Whom Naofumi Tomita trusts overall

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

1. Kaiming He
2. Shaoqing Ren
3. Geoffrey E. Hinton
4. X. Zhang
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Rob Fergus
8. Ross B. Girshick
9. Yann LeCun
10. Matthew D. Zeiler

Papers from Naofumi Tomita's perspective

Ordered by how strongly the researchers Naofumi Tomita 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 Large Scale Visual Recognition Challenge
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Microsoft COCO: Common Objects in Context
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks (2019) — 309 citations
• Deep neural networks for automatic detection of osteoporotic vertebral fractures on CT scans (2018) — 254 citations