E. Cha

Computer Vision and Pattern Recognition · 2017

A researcher in the Science corpus: 1 paper; trusts 45 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it; #14,463 of 21,575 by trust here, #16,787 by citations
• Artificial Intelligence — 10 citations into it
• Model Architectures — 7 citations into it
• Radiology, Nuclear Medicine and Imaging — 7 citations into it
• Computational Mechanics — 5 citations into it; #6,464 of 10,001 by trust here, #6,582 by citations

Whom E. Cha trusts overall

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

1. Ingrid Daubechies
2. Jian-Feng Cai
3. Stéphane Mallat
4. Diederik P. Kingma
5. Kaiming He
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Yann LeCun
9. Yoshua Bengio
10. Jimmy Ba

Who trusts E. Cha overall

1. Yoseob Han

Papers from E. Cha's perspective

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

Their papers

• Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems (2017) — 328 citations