Arnaud Arindra Adiyoso Setio

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 6 papers; trusts 32 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 130 citations into it; #16,649 of 21,575 by trust here, #1,669 by citations
• Artificial Intelligence — 100 citations into it; #34,046 of 35,345 by trust here, #2,401 by citations
• Model Architectures — 27 citations into it
• Optimization & Training — 24 citations into it

Whom Arnaud Arindra Adiyoso Setio trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Kaiming He
5. Ilya Sutskever
6. Yann LeCun
7. Xavier Glorot
8. Diederik P. Kingma
9. Ruslan Salakhutdinov
10. X. Zhang

Who trusts Arnaud Arindra Adiyoso Setio overall

1. B. van Ginneken
2. Fangzhou Liao
3. Lequan Yu
4. Evgin Göçeri
5. Yin Dai
6. Qi-Yan Dou
7. Dinggang Shen
8. Geert J. S. Litjens
9. Hao Chen
10. Marysia Winkels

Papers from Arnaud Arindra Adiyoso Setio's perspective

Ordered by how strongly the researchers Arnaud Arindra Adiyoso Setio trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A survey on deep learning in medical image analysis (2017) — 13,846 citations
• Memory-centric accelerator design for Convolutional Neural Networks (2013) — 315 citations
• Using deep learning to segment breast and fibroglandular tissue in MRI volumes (2017) — 204 citations
• Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks (2016) — 1,170 citations
• Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge (2016) — 1,345 citations
• Towards automatic pulmonary nodule management in lung cancer screening with deep learning (2016) — 392 citations