Yong-Deok Kim

Computer Vision and Pattern Recognition · 2015

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it; #19,870 of 21,575 by trust here, #5,161 by citations
• Artificial Intelligence — 25 citations into it
• Model Architectures — 10 citations into it
• Signal Processing — 7 citations into it
• Computational Mechanics — 5 citations into it

Whom Yong-Deok Kim trusts overall

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

1. X. Zhang
2. Kaiming He
3. Song Han
4. Geoffrey E. Hinton
5. Christian Szegedy
6. Yoshua Bengio
7. Yann LeCun
8. Alex Krizhevsky
9. David John Cameron MacKay
10. Sergey Ioffe

Who trusts Yong-Deok Kim overall

1. Shaohui Lin
2. Tien-Ju Yang
3. Jean Kossaifi
4. Yang He
5. Vivienne Sze
6. Breton L. Minnehan
7. Fahad Lateef
8. Yerlan Idelbayev
9. Peisong Wang
10. Zirui Wang

Papers from Yong-Deok Kim's perspective

Ordered by how strongly the researchers Yong-Deok Kim 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications (2015) — 949 citations
• Big/little deep neural network for ultra low power inference (2015) — 151 citations