Juhan Nam

Computer Vision and Pattern Recognition · 2011–2020

A researcher in the Science corpus: 4 papers; trusts 81 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 23 citations into it
• Signal Processing — 19 citations into it; #5,390 of 7,572 by trust here, #3,673 by citations
• Artificial Intelligence — 17 citations into it; #6,788 of 35,345 by trust here, #2,522 by citations
• Speech & Audio — 8 citations into it
• Model Architectures — 7 citations into it

Whom Juhan Nam trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Sergey Ioffe
4. Yoshua Bengio
5. Sander Dieleman
6. Alex Krizhevsky
7. Honglak Lee
8. Andrew Zisserman
9. Christian Szegedy
10. Keunwoo Choi

Who trusts Juhan Nam overall

1. Yuxin Peng
2. Li Deng
3. Ruslan Salakhutdinov
4. Yao-Hung Hubert Tsai
5. Ryan Kiros
6. Gabriella Csurka
7. Honglak Lee
8. Graham W. Taylor
9. Dario Rethage
10. Mingsheng Long

Papers from Juhan Nam's perspective

Ordered by how strongly the researchers Juhan Nam 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Multimodal Deep Learning (2011) — 3,550 citations
• Children's Song Dataset for Singing Voice Research (2020) — 48 citations
• Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging (2017) — 149 citations
• Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms (2017) — 206 citations