Benjamin Q. Huynh

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it; #32,790 of 35,345 by trust here, #14,181 by citations
• Computer Vision and Pattern Recognition — 11 citations into it

Whom Benjamin Q. Huynh trusts overall

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

1. Jeff Donahue
2. Jason Yosinski
3. Yoshua Bengio

Who trusts Benjamin Q. Huynh overall

1. Berkman Sahiner
2. Geert J. S. Litjens
3. Mainak Biswas
4. Maryellen Lissak Giger
5. Mengying Shu
6. Aria Pezeshk
7. Maciej A. Mazurowski

Papers from Benjamin Q. Huynh's perspective

Ordered by how strongly the researchers Benjamin Q. Huynh 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. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• A Deep Feature Fusion Methodology for Breast Cancer Diagnosis Demonstrated on Three Imaging Modality Datasets (2017) — 358 citations
• Digital mammographic tumor classification using transfer learning from deep convolutional neural networks (2016) — 486 citations