Nick Hynes

Computer Vision and Pattern Recognition · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 123 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 37 citations into it
• Artificial Intelligence — 24 citations into it
• Natural Language Processing — 14 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Multimodal Learning — 11 citations into it
• Model Architectures — 6 citations into it

Whom Nick Hynes trusts overall

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

1. Ilya Sutskever
2. Kaiming He
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Oriol Vinyals
6. Alex Krizhevsky
7. Tomas Mikolov
8. Yoshua Bengio
9. Andrew Zisserman
10. Andrej Karpathy

Who trusts Nick Hynes overall

1. Amaia Salvador
2. Fadime Sener
3. Peiqin Zhuang

Papers from Nick Hynes's perspective

Ordered by how strongly the researchers Nick Hynes 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. Going deeper with convolutions

Their papers

• Learning Cross-Modal Embeddings for Cooking Recipes and Food Images (2017) — 316 citations
• Recipe1M: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images (2018) — 386 citations